Smart Region Technologies:
A Taxonomy and Overview Report
September 2019
Disclaimer This report was funded in part through grant[s] from the Federal Highway Administration and/or Federal Transit Administration, U.S. Department of Transportation. The contents of this report reflect the views and opinions of the author(s) who is responsible for the facts and accuracy of the data presented herein. The contents do not necessarily state or reflect the official views or policies of the U.S. Department of Transportation, the Arizona Department of Transportation, or any other State or Federal Agency. This report does not constitute a standard, specification or regulation.
The information in this publication is provided on an “as is” basis, and there are no warranties, express or implied, including, but not limited to, any warranties of merchantability or fitness for a particular purpose. In no event shall MAG be liable for any damages resulting from the use of the information. MAG provides the information in good faith and has endeavored to create and maintain accurate data. The users of this report and/or data are advised to use the information with caution and to independently verify accuracy.
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Table of Contents
1 Planning for Transformational Changes: A Regional Perspective ...... 1 1.1 Introduction and Goals of the Report ...... 1 1.2 Developing a Smart Region Framework for MAG ...... 5 1.3 Application Domains ...... 7 1.4 Organization of the Report ...... 10 2 Smart City Initiatives and Efforts in Arizona ...... 11 2.1 Examples ...... 11 2.2 Statewide Technology Deployment ...... 32 2.3 Micromobility in Cities ...... 35 2.4 Demonstrations of Automated Micromobility in the Valley ...... 36 2.5 Smart Street Lighting...... 37 3 Smart Mobility ...... 39 3.1 Intelligent Transportation Systems (ITS) ...... 39 3.2 Ride Sharing and Ride Hailing Systems ...... 43 3.3 Connected and Autonomous Vehicles ...... 45 3.4 Smart Parking ...... 46 3.5 Wireless Signal Tracking ...... 47 3.6 Smart Bus Operations ...... 48 3.7 Electronic Toll Collection ...... 48 3.8 Unmanned Aerial Systems or Vehicles (UAS or UAV) ...... 49 3.9 Hyperloop ...... 50 3.10 Advanced Data Analytics ...... 51 4 Examples of Smart Transportation Applications ...... 51 4.1 Holistic Smart Transportation Deployment Initiatives ...... 51 4.2 Examples of Emerging Mobility Technologies – Shared, Automated, and Electric ...... 55 4.3 Data and Information Systems ...... 58 4.4 Streets and Lighting ...... 60 5 Smart Technologies in Non-Transportation Domains ...... 62 5.1 Smart Health ...... 62 5.2 Smart Buildings ...... 63
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5.3 Smart Governance ...... 64 5.4 Smart Energy ...... 65 5.5 Smart Water Management ...... 66 5.6 Smart Waste Management ...... 66 5.7 Smart Communication ...... 68 5.8 Smart Education Systems ...... 72 6 Developing a Vision and Action Plan ...... 73 6.1 Summary...... 73 6.2 SWOT Analysis ...... 73 6.3 Next Steps ...... 75 7 References ...... 76
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List of Figures Figure 1.1 Five core areas in the MAG FY 2020-2021 Unified Planning Work Program & Annual Budget...... 2 Figure 1.2 Vision elements of the Austin Texas smart city plan (City of Austin, 2016) ...... 4 Figure 1.3 Greater Washington smart city goals (Greater Washington Board of Trade, 2018) ...... 5 Figure 1.4 MAG’s smart region direction ...... 6 Figure 2.1 Greater Phoenix smart region framework (Arizona Institute for Digital Progress, 2019) ...... 12 Figure 2.2 50th Street Station (Valley Metro, 2019b) ...... 13 Figure 2.3 PAG smart region goals (PAG, 2018b) ...... 15 Figure 2.4 Freight plan (PAG, 2018a) ...... 16 Figure 2.5 Mesa smart city foundation (City of Mesa, 2018a) ...... 18 Figure 2.6 Mesa smart city plan (City of Mesa, 2018b) ...... 19 Figure 2.7 Map of intersections with bike detection within Scottsdale (City of Scottsdale, 2019a) ...... 21 Figure 2.8 Road users detection and tracking using AI technology to measure PET at the conflict point ... 22 Figure 2.9 Smart city challenge: Tucson, AZ vision statement (City of Tucson, 2016) ...... 24 Figure 2.10 Smart city challenge: Tucson, AZ vision statement (City of Tucson, 2016)...... 25 Figure 2.11 City of Tempe: vision zero (City of Tempe, 2019c) ...... 27 Figure 2.12 Approximate location of Belmont (Weiner, 2017) ...... 29 Figure 2.13 Bike share in city of Flagstaff (Skabelund, 2018) ...... 30 Figure 2.14 Connected fire truck (MCDOT, 2019b) ...... 31 Figure 2.15 DSRC sensor...... 32 Figure 2.16 Bell Road adaptive signals (MCDOT, 2019a) ...... 32 Figure 2.17 Waymo autonomous vehicle in Arizona (Cnet, 2019) ...... 34 Figure 2.18 Waymo autonomous truck (Cnet, 2019) ...... 34 Figure 2.19 Micro mobility type of transportation in city of Gilbert (City of Gilbert, 2019) ...... 35 Figure 2.20 Olli Automated shuttle by local motors (Bhuiya, 2016) ...... 36 Figure 2.21 Nuro Grocery delivery shuttle (Russ Wiles, 2019) ...... 37 Figure 2.22 Yuma smart lighting (City of Yuma, 2019) ...... 38 Figure 3.1 Illustration of Broadcasting Traffic Signal Information to Vehicles ...... 42 Figure 3.2 Concept of Uber Elevate (Uber, 2019) ...... 49 Figure 3.3 A Rendering of the Hyperloop Transportation System (Hyperloop, 2019) ...... 50 Figure 4.1 North Florida smart region plan framework (North Florida TPO, 2017) ...... 52 Figure 4.2 City of Columbus goals (U.S. DOT, 2016a) ...... 53 Figure 4.3 Denver's smart city program (City of Denver, 2016) ...... 54 Figure 4.4 Oregon smart city technology foundation diagram (City of Portland, 2016) ...... 55 Figure 4.5 Autonomous vehicle pilot test in Las Vegas (Las Vegas City Hall, 2019) ...... 58 Figure 4.6 Kansas smart city vision (City of Kansas City, 2016) ...... 59 Figure 4.7 Smart street lighting framework (Illinois DOT, 2019) ...... 61 Figure 4.8 Operation of San Diego smart light fixtures (City of San Diego, 2019) ...... 61 Figure 5.1 Barcelona smart Irrigation system example (Libelium, 2016) ...... 64 Figure 5.2 Smart waste management system outline (Aazam et al., 2016) ...... 67 Figure 5.3 Outline of a smart garbage disposal process (Yusof et al., 2017)...... 68 Figure 5.4 M2M Cellular Solutions Diagram (UNICOM Global, 2019) ...... 69
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Figure 5.5 Smart Communication Networks overview (Al-Fuqaha et al., 2015) ...... 70 Figure 5.6 Components of IoT (Hikumwa, 2018) ...... 71 Figure 6.1 SWOT analysis ...... 74
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List of Tables Table 1.1 Domains and Technologies ...... 10 Table 2.1 Tucson Smart City Goals (City of Tucson, 2016) ...... 22 Table 3.1 Examples of Mobility-as-a-Service ...... 44 Table 3.2 CAV Data Platform Examples ...... 46 Table 3.3 Smart Parking Applications ...... 47 Table 3.4 Examples of Wireless Signal Tracking Device ...... 48 Table 4.1 San Francisco Smart City Key Outcomes (City of San Francisco, 2016) ...... 56
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1 Planning for Transformational Changes: A Regional Perspective
1.1 Introduction and Goals of the Report
Many regions around the world are seeking to harness the power of rapidly evolving technology to improve quality of life, foster economic development, support businesses and improve effectiveness and efficiency of governmental organizations. Some of the technological advancements are well founded and verified and can bring about the promised change for the better, others need further research and improvements and yet other ones are overinflated hype that can actually be damaging and distract resources and efforts from more productive venues (Saxe, 2019).
Metropolitan Planning Organizations (MPOs) and regional Councils of Governments (COGs) across the country are looking into the Smart Region phenomena and trying identify the most promising technological solutions to the most pressing problems and separate the hype from the “real deal”. The regional agenda that they are pursuing is often unique, more complex and somewhat different from the “Smart City” efforts, in the sense that MPOs and COGs are dealing with multiple jurisdictions and numerous, sometimes contradicting, demands and needs. Regional infrastructure plans, in particular transportation infrastructure plans, need to ensure a cooperative approach that satisfies multiple stakeholders and at the same time provides required levels of service for people and businesses. Traveling public might not necessarily be aware of crossing jurisdictional boundaries while traveling in the region. This regional perspective adds a number of new criteria to the selection of technological investments. Considerations about regional scalability, feasibility of regional deployment, acceptance by regional agencies’ boards, regional maintenance and operations, regional benefits and costs and regional scale problems will play the most important role in the development of the regional infrastructure investment plans.
The Maricopa Association of Governments (MAG) is a Metropolitan Planning Organization and a Council of Governments that serves as the regional planning agency for the metropolitan Phoenix area. As the regional planning agency and a forum of local governments, MAG seeks to deploy technologies that can make the region prosper and be smarter, more sustainable, and more resilient. MAG has identified five core value areas in the Fiscal Year (FY) 2020-2021 Unified Planning Work Program (UPWP), the guiding planning document for the time period. The core areas (Figure 1.1) and the priority outcomes will all be affected by future technology decisions and developments.
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Figure 1.1 Five core areas in the MAG FY 2020-2021 Unified Planning Work Program & Annual Budget
A balanced and fruitful approach calls for closely monitoring rapidly evolving state-of-the- practice, identifying, piloting and evaluating promising emerging technologies and keeping the important needs of the residents at the forefront of decision making. Local, regional, state and federal planning agencies are all proactively investigating emerging technologies and application domains and work closely with businesses, researchers and other governments in these directions. MAG has been and is involved in numerous collaborative efforts with the agencies across the state and nation-wide that look at different aspects of the ongoing transformational disruptive changes, from planning for autonomous and connected vehicles to connected vehicles to smart infrastructure experiments, from traffic management solutions to forecasting future scenarios to emerging technologies, from advanced data collections and analytics to innovative methods of inter-governmental cooperation.
MAG is currently working on the development of the new Regional Transportation Plan (RTP) and preparing for a proposed transportation sales tax extension. Planning transportation investments requires understanding of emerging technologies and the role that they can play in the future. A number of specific technical efforts have been initiated by MAG in order to support the plan development. MAG FY 2020-2021 UPWP and Annual Budget include projects under the Regional System Management and Operations Plan, Transportation Safety Plan, the Emerging
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Technologies Field Pilots On-Call program and the Public University Task Force. All these initiatives include identification, deployment and evaluation of the Smart Region technologies. Results of these undertakings will provide input in the development of the new RTP.
Goals of this report are two-fold. First, this report is taking a look at the current state of the practice in Smart City and Smart Region areas in Arizona with emphasis on MAG region. This report also looked at many prominent examples from around the country. This report fully realizes that new applications and noteworthy examples are emerging at the time of writing and the field is rapidly developing. Therefore, this report does not pretend to provide an all- encompassing or a long-lasting picture. It rather strives to provide a solid snapshot of the existing situation and inform upcoming planning and implementation efforts in the area in the near future. Second, this document provides analyses relevant to the regional planning agenda and suggest a taxonomy of technologies and applications that can be instrumental for the regional planning purposes and lay a foundation for the Smart Region Framework.
Just to give a flavor of the initiatives and efforts discussed in this report, below are a few notable examples of Smart City and Smart Region developments.
Austin, Texas is seeking to address some of its issues with smart city technologies. These issues include high poverty rates, isolated neighborhoods, scarce educational opportunities, and low employment levels. In order to address these issues, Austin hopes to connect underserved communities to the resources they need to thrive. This will be achieved by introducing electric public transportation fleets and connected automated vehicles specifically targeted at under- served communities (U.S. DOT, 2016b). The Vision Elements of the Austin Texas Smart City Plan are shown in Figure 1.2. The plan is largely centered around transportation (because the plan was put forth as part of the USDOT Smart City Challenge), but includes a number of other components including a smart grid for roadway electrification and electric vehicle uptake, connected and involved citizens, updated cyber architecture and standards, low-cost and resilient Image result for information and communications technology (ICT), and smart land use that facilitates a reduction of carbon footprint.
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Figure 1.2 Vision elements of the Austin Texas smart city plan (City of Austin, 2016)
Similarly, in the Washington D.C. metropolitan area, the Greater Washington Board of Trade has begun a movement to establish itself as a smart region in the hope of improving the quality of life for its citizens. Its goals are outlined in Figure 1.3.
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Figure 1.3 Greater Washington smart city goals (Greater Washington Board of Trade, 2018)
The Greater Washington Board of Trade is striving to achieve these goals through these strategies: • Analytical research and studies • Case studies and best practices • Pilots and demonstrations (Greater Washington Board of Trade, 2018)
The Greater Washington metropolitan area has already made strides towards becoming a smart city. The metro area has installed bike sharing programs and has worked to improve the communication and information systems for the Washington Metro. To manage and control wastewater and runoff, Greater Washington installed underground sensors to alert the municipality of any leaks or problems.
There are a number of other examples from around the country, largely focused on transportation and mobility. They are reviewed later in this report in the context of more detailed discussions and descriptions of smart transportation technologies.
1.2 Developing a Smart Region Framework for MAG
MAG region is a highly interconnected conglomerate of jurisdictions with both disparate and shared priorities. MAG is in a unique position to promote a holistic and integrated region-wide
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approach to smart city development, essentially driving a smart region development effort that would move the entire region toward improved coordination, consistency and efficiency in technologies and relevant guidelines across jurisdictions. The five core areas (Figure 1.1) can be transpired into different aspects of the Smart Region applications or different system-forming factors (Figure 1.4).
Figure 1.4 MAG’s smart region direction
Consideration for all these factors is important in order to ensure that new technologies are properly evaluated for the purposes of regional planning. Political, economic, social, technological, legal, environmental, and organizational and informational factors play an important role in shaping the region and fulfilling the core areas of activities. Implementing smart region technologies can help to address multiple core values simultaneously, such as improving the economy, increasing employment opportunities, reducing crime, enhancing organizational efficiency, and increasing living comfort.
Looking at the Smart Region solutions, it should be noted that the key elements that almost always are present include detection (with relevant data processing, often involving machine learning) and connectivity between the detectors. These improvements normally lead to a better service and a better product, which in our context usually means better transportation services and a better infrastructure. The primary solutions and technologies that often comprise a smart region initiative include, but are not limited to, the Internet of things (IoT), innovative sensors for big data collection (in any domain of interest), artificial intelligence (and machine learning in particular), and Delivery of Anything (including mobility) as a Service (XaaS). IoT is often a low
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cost, high network density data transferring mechanism. IoT does not require human-to-human or human-to-computer interaction. The innovative sensor can collect big data automatically and efficiently. Artificial intelligence provides the ability to mine large amounts of data, potentially in real-time, and derive actionable predictive analytics to help elevate system performance on a continuous basis. XaaS is a technology that refers to the delivery of anything as a service. XaaS acts as a smart network that allows vendors and businesses to deliver products, tools, services, and technologies over a network to customers. All of these developments can be used to increase connectivity between devices and improve the functionality and efficiency of different processes.
The power of IoT, innovative sensors, big data collection tools, artificial intelligence and XaaS technologies can be harnessed in multiple application areas. They are grouped into nine application domains of interest within the scope of this effort, including smart transportation, smart health network, smart safety, smart services, smart energy, smart water management, smart waste management, smart communication systems, and smart education systems.
1.3 Application Domains
1.3.1 Linking all the Domains Overall, new smart technologies allow for better communication between devices, better identification of problems, and improved methods of collecting massive amounts of data. Advances in smart communication will transform the transportation, water management, waste management, buildings, healthcare, health networks, energy, and education domains by allowing faster data exchange between and within each domain. This will make problems easier to identify and address and improve the response time necessary to address problems that occur. This will increase efficiency and productivity. All these advances, in turn, create a smart governing body which has the power to access information on all domains easily, be informed of problems and complications as they appear, and be able to address the problems as efficiently and adequately as possible.
1.3.2 Domains and Outcomes Each application domain can often fulfill multiple core values and regional goals. In other words, many smart systems and components can advance multiple goals simultaneously, as long as any unintended consequences are adequately mitigated. For example, the growing use of ride- hailing services (and, in the future, automated vehicles) may contribute to more vehicle miles of travel, especially empty vehicle miles of travel as vehicles cruise around waiting and search for the next ride. This growth in vehicle-miles of travel does not advance a regional core value, but could be addressed by deploying technologies, policies and regulations that minimize such zero-occupant vehicle mileage, help match multiple riders with similar origin-destination patterns into a single vehicle (greatly enhancing sharing), and enable ride-hailing services to provide effective, convenient, and low cost first-mile/last-mile connectivity to transit.
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The following is a brief description of each smart region domain. It should be noted that the description is not intended to be comprehensive and exhaustive. The domains are vast, and the technologies are rapidly evolving. As such, it is impossible to provide a comprehensive treatment of every domain within the scope of this document. A few illustrative systems of each domain are mentioned here to provide some clarity on the types of systems that may be considered and the benefits they can provide. Additionally, there is much overlap between individual systems and domains, so it is not uncommon to see one system appear in multiple domains. Smart Transportation • Advanced traffic management systems and connected autonomous vehicles will significantly improve transportation safety by decreasing crash rates and promoting smoother traffic flow. • Ride-sharing and hailing systems could improve sustainability by taking privately owned vehicles off of the roadways and engendering shared rides. • Smart traffic signals and dynamic mobility applications will optimize traffic flow and improve efficiency (reduce delays, improve travel times). • Smart freight systems improve efficiency and reduce costs of deliveries and goods movement.
Smart Health • Pollution detection will provide the ability to target interventions and improve the health of exposed neighborhoods. • New online applications and interconnected health information networks will make health care easier to navigate. • New wrist watches can monitor and communicate critical organ functions and health indicators, making it easier to identify and respond to health concerns.
Smart Buildings • Buildings will be equipped with sensors to more effectively monitor temperature and occupancy, reducing energy costs for lighting and heating/cooling and enhance security. • New building designs can facilitate deliveries and address emerging trends in logistics to make freight more efficient and less intrusive for urban areas.
Smart Governance • Online transaction options will increase the accessibility of government functions. • Increased organizational efficiency and inter-connected automated systems will reduce bureaucracy and make civic functions more accessible and efficient. • Efficient exchange of information (often in real time) between different branches and departments (e.g. traffic, fire and police) can reduce service times and drastically improve efficiency.
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Smart Energy • Smart grids and smart meters will save on energy costs and increase sustainability and efficiency.
Smart Water Management • Smart chemical leakage detection and smart pollution control will reduce the chances of people being exposed to harmful chemicals. • New sensors that monitor water consumption will improve sustainability and efficiency by eliminating losses.
Smart Waste Management • Smart garbage and recycling systems will decrease the amount of solid waste produced by communities, improving the health of the environment. • Smart trash containers will alert the municipality when the containers are full, increasing the efficiency of trash collection routes.
Smart Communication Systems • The Internet of Things and other smart communication networks will improve the efficiency and safety of data exchange.
Smart Education Systems
• Adaptive learning systems and learning content management systems will greatly improve the efficiency and accessibility of current education systems. • Affordable education options will be available on-demand, thus creating greater opportunities for creating an educated population and economic growth.
Public Safety
• Smart lighting application enhances public safety (see examples from Las Vegas, NV in Section 4.2.3). • Better information sharing among first responders such as police, fire and ambulance.
1.3.3 Domains and Technologies The primary technologies mentioned earlier can help advance each of the smart region application domains, as shown Table 1.1. Some of the application domains, such as smart transportation, could easily take advantage of all of the proposed technologies. Almost all the application domains can utilize the internet of things.
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Table 1.1 Domains and Technologies
Outcomes IoT* Artificial XaaS ** Innovative Big Data Domains Intelligence Sensors Smart Transportation ✔ ✔ ✔ ✔ ✔ ✔ ✔ ✔ ✔ ✔ Smart Health Network ✔ ✔ ✔ ✔ Smart Buildings ✔ ✔ ✔ ✔ Smart Governance ✔ ✔ ✔ Smart Energy ✔ ✔ ✔ ✔ Smart Water Management Smart Waste ✔ ✔ Management ✔ ✔ ✔ ✔ Smart Communication Smart Education Systems ✔ ✔ ✔ ✔ Public Safety ✔ ✔ ✔ ✔ ✔ *Internet of Things; ** Anything-as-a-Service
In summary, smart city technologies have the potential to impact all of the different facets of everyday life, from transportation to education systems. Within the scope of this report, nine domains are selected based on the lessons learned, literature review, and consistency with MAG vision and core values. Figure 1.4 shows example application domains and their associated components in a summary format with a view to presenting a practical taxonomy that can guide future smart technology deployment strategies in the MAG region.
1.4 Organization of the Report
The remainder of this report is organized as follows. Chapter 2 presents an overview of smart city initiatives in Arizona. Because transportation is central to MAG’s mission, Chapter 3 is dedicated to describing smart transportation technologies with emphasis on mobility. The fourth chapter presents a number of case studies and examples of smart transportation technology deployments around the country to complement the descriptions presented in Chapter 3. The fifth chapter offers a description of all other smart technology domains for the sake of completeness, although it should be recognized that many of the smart technology applications are inter-related and should not be viewed within their own silos. Finally, the last chapter concludes with a few next steps that MAG may wish to pursue as it transforms the valley into a Smart Region. The list of references concludes the report.
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2 Smart City Initiatives and Efforts in Arizona
2.1 Examples
This Section outlines the smart city plans and initiatives taking place in Arizona. Similar to other states, the state of Arizona is also investing in smart technologies. Arizona is known for being a technology friendly state, and it is noted that a group of associates with Cascade Investment, an investment company controlled by Bill Gates, has invested $80 million in a west valley property with reports that the site coupled become a center of smart technologies in the Phoenix area.
Many major autonomous vehicle pioneers such as Waymo, TuSimple, Intel, and NURO are testing their driverless vehicles on Arizona highways. In addition, Arizona Governor Doug Ducey signed an Executive Order in 2018 creating the Institute for Automated Mobility (IAM), a collaborative of three major state universities, government agencies, the Arizona Commerce Authority, and the Greater Phoenix Economic Council, that would help advance autonomous vehicle testing and deployment in the state. Intel is one of the founding members of this consortium.
A select set of ongoing and planned initiatives are described in the following sections.
2.1.1 Greater Phoenix Smart Region Consortium Greater Phoenix is striving to become a smart and connected region to improve the quality of life for its citizens. The Greater Phoenix Economic Council (GPEC), Arizona State University (ASU), the Institute for Digital Progress (IDP), and MAG are collaborating through Greater Phoenix Smart Region Consortium to drive the creation, advancement and adoption of smart city technology that improves the quality of life for all citizens and businesses within Greater Phoenix communities. To support sustainable, resilient, healthy, and equitable communities and neighborhoods, this initiative aims to transform the Greater Phoenix region into a global leader in public-sector governance and private sector innovation by forming a unique collaborative applied research and implementation partnership between public-sector, academia, industry and civic institutions. The framework for this Initiative is outlined below in Figure 2.1. Going forward, it is envisioned that MAG will play a key role in bringing cities and stakeholders together, identifying promising technologies for possible testing and deployment in the region, and conducting field-tests of alternative technologies to evaluate their efficacy in meeting goals and enhancing system performance.
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Figure 2.1 Greater Phoenix smart region framework (Arizona Institute for Digital Progress, 2019)
Regional objectives include a new digital road map that will connect all of the communities within Greater Phoenix, making autonomous vehicles available for public use once they are deemed safe, creating a new policy to address rising temperatures, and installing smart energy systems. These goals will be accomplished through the combined efforts of the Greater Phoenix Smart Region Consortium, Arizona State University Center for Smart Cities and Regions (CSCR), the Arizona Institute for Digital Progress (IDP), Arizona Commerce Authority, and the Greater Phoenix Economic Council (TechConnect, 2018).
In addition, Arizona State University established the ASU Smart City Cloud Innovation Center (CIC) powered by Amazon Web Service (AWS), an initiative that focuses on building smarter communities in the Phoenix metropolitan area by using AWS Cloud to solve pressing community and regional challenges. The new center is designed as part of a long-term collaboration between ASU and Amazon Web Services to improve digital experiences for smart city designers, expand technology alternatives while minimizing costs, spur economic and workforce development and facilitate sharing public-sector solutions within the region.
The City of Phoenix is undertaking a number of initiatives as well. A few examples are noted below. Phoenix Bike Share Programs The City of Phoenix permits three bike share vendors to operate within its city limits. The vendors include:
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● GRID bike ● LIME bike ● PACE Bikes These vendors provide bikes that individuals can share and use for a fee, promoting bicycle use by making cycling more accessible and affordable (City of Phoenix, 2019a). City of Phoenix Partnership with Lyft The City of Phoenix is partnering with Lyft as part of a first-mile last-mile campaign. Lyft provides a discount for trips to specific transit stations.
2.1.2 Valley Metro Valley Metro is the public transit agency for the metropolitan area, and has engaged in various smart initiatives, as detailed below (Valley Metro, 2019a). 50th Street Station Valley Metro completed a new light rail station with enhanced Americans with Disabilities Act accessibility. This station is located in Phoenix at 50th and Washington, and has many features designed to increase the mobility of citizens with disabilities. Of note to this document is the implementation of a crosswalk with enhanced pedestrian detection capabilities (Valley Metro, 2019b).
Figure 2.2 50th Street Station (Valley Metro, 2019b)
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Ridekick app The Ridekick app is the mobile app for Valley Metro, and it provides easy navigation and interactive trip planning for users. It provides users with all the information they need to successfully take advantage of public transportation (Valley Metro, 2019c). Waymo Partnership Valley Metro has entered into a partnership with Waymo to provide first-mile and last-mile connectivity to and from transit stops and stations and park and ride facilities. Waymo is an automated vehicle service provider that has launched an early rider program in the East Valley to test and prove the effectiveness of automated vehicles as a viable means of transportation. Valley Metro is a significant partner in the early rider program and working with Waymo to expand the service, with the objective of using automated vehicles to increase transit ridership.
2.1.3 Maricopa Association of Governments (MAG) The Maricopa Association of Governments (MAG) is coordinating a number of regional efforts to ensure that smart technologies are planned, designed, and implemented in a way that enhances regional connectivity and consistency. Recently, MAG used artificial intelligence and video systems to collect footage of near-miss conflicts between pedestrians and vehicles. MAG works closely with partners in the region to deploy intelligent transportation systems, including sensors and real-time information systems, with a view to enhance mobility and empower travelers.
2.1.4 Pima Association of Governments (PAG) The Pima Association of Governments (PAG) has created a Smart Region plan which focuses on six different areas of improvement that include: water reliability, strategic talent alignment, infrastructure resilience, advanced communication infrastructure, modern transportation system development, and a shared regional vision. PAG smart region goals are illustrated in Figure 2.3.
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Figure 2.3 PAG smart region goals (PAG, 2018b)
In order to accomplish their goals, PAG has developed several potential strategies, including free WiFi kiosks, smart corridors, smart water meters, and the implementation of a smart grid (PAG, 2018b). 2018 Regional Freight Plan In the adopted 2018 regional freight plan, PAG decided to explore signal timing improvements and freight vehicle prioritization on regional freight corridors. They also decided to upgrade communication technology on traffic signals for improved signal coordination in preparation for vehicle to infrastructure connectivity. They also will identify corridors to pilot new transportation technologies. The table in Figure 2.4 outlines several strategies PAG will use to achieve their goals (PAG, 2018a).
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Figure 2.4 Freight plan (PAG, 2018a)
Sun Rideshare Sun Rideshare is a free commuter assistance program provided by PAG. It provides people living in the PAG region with alternative travel options. The program offers the following services (Sun Rideshare, 2019):
• Carpooling • Vanpooling • Public transit • Commute cost calculator • Commuter matching database Pima Commuter School Pool Pima Commuter School Pool is a free online service provided by PAG that connects the parents of children who live in the same area and attend the same school for carpooling. This reduces congestion, pollution, and assists parents with driving responsibilities (PAG, 2019).
2.1.5 Chandler, AZ Chandler, Arizona has rapidly become a testbed for autonomous vehicles. Some of the leading companies operating in Chandler are Waymo, Intel (Mobileye), NXP Semiconductor, General
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Motors, Maxim Integrated, Microchip Technology, Rogers Corporation, and Garmin. Waymo brought its self-driving vehicles to Chandler in 2016 (City of Chandler, 2019a). Ride-Hailing Service Chandler is partnering with Waymo to offer a ride-hailing service to city employees for one year. The City of Chandler is also considering allowing e-scooter and bike-sharing in the city. They are doing surveys to gather user opinion over e-scooters and bike-sharing services operating in cities across the country. Smart Transportation Solutions Chandler has partnered with Waze for traffic data collection. Residents are encouraged to download the Waze app for driving directions, traffic reports, and carpooling options.
The City of Chandler has also placed Dynamic Message Signs at strategic freeway entrance points to provide commuters with travel time information. This helps reduce congestion because drivers are aware of congested areas in advance, and they can avoid such bottlenecks.
Also, to reduce traffic crashes and red light running, Chandler implemented a red-light photo enforcement program at a number of signalized intersections. Warning signs are placed approximately half a mile before photo enforced intersections, and fines are levied in a manner that ensures the program is revenue neutral. In this way, Chandler is focusing the program on safety enhancement (rather than revenue generation).
2.1.6 Mesa, AZ In 2018, Mesa enlisted Think Big Partners, LLC to help develop a Smart Mesa master plan. Mesa desires to use new technologies to improve the quality of life for its citizens. The Mesa smart city foundation is pictured in Figure 2.5 (City of Mesa, 2018a). Smart Downtown Pilots The city of Mesa is currently working on the following projects to improve its downtown traffic conditions. The projects listed are still in the development and planning stages and will be initiated within the next 18 to 24 months (City of Mesa, 2019a).
• Broadband and Wi-Fi Expansion The city will provide gigabit fiber and Wi-Fi connectivity to the downtown area to improve connectivity.
• Digital Kiosks The city will install digital kiosks downtown that provide information on tourist attractions, wayfinding, and light rail travel.
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• Parking sensors The downtown parking spaces will be equipped with sensors so that citizens are alerted of available spots through a smart-phone app. This will reduce congestion and enhance traffic flow.
• Shared Active Transport Vehicles (SATV) Shared Active Transport Vehicles include e-scooters and e-bikes, and they provide citizens with inexpensive modes of travel that reduce vehicular congestion.
Figure 2.5 Mesa smart city foundation (City of Mesa, 2018a)
In addition to the above, Mesa has developed or is in the process of developing a number of smart city technologies for implementation in the city. The following is an abbreviated list of technologies as outlined in the Mesa Smart City Plan (City of Mesa, 2018b):
Transportation: • Compatible Camera Systems • Intelligent Traffic Systems – The continued deployment of sensors and data networking • Waymo – Waymo is expanding its service into Mesa, Arizona. The Mesa Technical Service Center is projected to occupy 85,000 square feet (Randazzo & Collom, 2019).
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Non-Transportation: • LED Lighting Pilot & Study – Deployment of high efficiency LED lights capable of controlling the light temperature and supplying a place to power and connect antennas and smart sensors. • Park Enhancements: o Smart Irrigation o WiFi availability • Mobile App - MesaNow mobile app provides a central hub for services and information • Data Governance & Open Data - A type of open data management for city management data, including Open Budget, Open Expenditures, City Council Strategic Priorities, and datasets related to Energy & Utilities, Permits & Licenses, Financials, Recreation & Culture, Zoning & Property, Neighborhoods, Public Safety, Transportation/ Transit, and OpenGIS. • Facilities Automation - Enhance existing building automation system and add sensors to automate and monitor HVAC, lighting, security, life safety, and other building functions. • Food-to-Energy Anaerobic Waste Digester Pilot - Pilot converting food waste processed through the city’s anaerobic digester to produce energy ultimately. • Thinkspot –in all City Libraries, allowing innovative citizens free or inexpensive access to the tools of creation.
Mesa is continuing to work on refining the smart city plan and building the necessary infrastructure to enhance quality of life for residents and visitors. Figure 2.6 depicts the plan that is being put in place.
Figure 2.6 Mesa smart city plan (City of Mesa, 2018b)
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2.1.7 Scottsdale, AZ The City of Scottsdale, Arizona is one of the cities that participated in the USDOT Smart City challenge to address “how emerging transportation data, technologies, and applications can be integrated with existing systems in a city to address transportation challenges” (City of Scottsdale, 2015).
Eight major areas that the City of Scottsdale identified in the challenge were:
1. Develop ultra-smart corridors – two of the most congested multimodal corridors are selected to assess the mobility of auto, electric vehicle, semi-autonomous auto, autonomous auto, transit, bike, and pedestrian, with a view to elevating them to smart corridors 2. Development of smart infrastructure that would support Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I) communications 3. A test-case that addresses multimodal transportation for the disadvantaged 4. Development of a user interface using crowdsource data to provide an interactive real-time platform for a user to determine a more socially responsible route 5. Smart preemption at traffic signals to favor transit and ride-share vans 6. Further exploit the interplay of bike/pedestrian technology to promote use of non- motorized modes of transportation 7. Enhancing paratransit, fixed transit, and trolley routing designed for elderly people 8. Evaluating system constraints and intersection signal prioritization
In addition to these desired areas of focus for the future, Scottsdale has implemented the following applications as listed in the successive sections. Bicycle Signal Detection The City of Scottsdale is installing sensors to detect bikes at intersections to improve bicyclist safety, as shown in Figure 2.7. Currently 13 intersections have been programed with bicycle video detection technology. The city hopes safe intersections will promote bicycling and reduce vehicular congestion (City of Scottsdale, 2019a).
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Figure 2.7 Map of intersections with bike detection within Scottsdale (City of Scottsdale, 2019a)
NextRide Scottsdale citizens can access information on the closest available rail and bus travel options by using NextRide, a service that only requires a phone or access to the internet, along with the route number and stop number (valley Metro, 2019d). Scottsdale Trolley Scottsdale offers a free trolley system that links citizens to cultural, recreational, and educational facilities. There are four routes in the system, and the arrival and departure times can be accessed through Valley Metro’s data systems (City of Scottsdale, 2019b). Multimodal Safety As vulnerable road users are overrepresented in fatal and serious injury crashes, a greater understanding of their behavior can help agencies construct better infrastructure to accommodate their needs while reducing the frequency of fatal and serious injuries. The City of Scottsdale conducted a study utilizing computer vision and artificial intelligence to collect multimodal surrogate safety information in absence of crash data and recommend proactive safety countermeasures. Artificial Intelligence technology identified near-miss collisions by determining post-encroachment time (PET) between users, defined as the time lapse between two road users crossing the same location. A potential conflict was identified by the detection
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system when the PET was less than 3 seconds. In addition, each conflict was further classified by whether the pedestrian / bicyclist or motorist arrived first at the conflict point. It was perceived to be more dangerous if the pedestrian or bicyclist arrived first because they were not in control of the time lapse between themselves and the vehicle(s). This helped to categorize the potential for a serious injury to the pedestrian. The study revealed promising results by utilizing AI technology that can allow for dangerous situations involving pedestrians to be detected and paves the way for proactive improvements in pedestrian safety. Figure 2.8 shows the detection and tracking of road users using AI technology to measure the PET at the conflict point
Figure 2.8 Road users detection and tracking using AI technology to measure PET at the conflict point
2.1.8 Tucson, AZ In response to the USDOT Smart Cities Challenge of 2016, Tucson proposed several solutions to its transportation safety and congestion challenges (Table 2.1). These solutions included: installing smart LED street lights, optimizing signal priority for first responders, introducing autonomous vehicles, and optimizing freight travel performance (City of Tucson, 2016) Table 2.1 Tucson Smart City Goals (City of Tucson, 2016)
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2016 Smart City Initiative In response to the smart city challenge of 2016, the City of Tucson identified its greatest traffic challenges (City of Tucson, 2016):
• 14th worst congested city in the nation • 9th highest percent of commuters • 75% of vehicle miles are traveled on arterials • 10% of roadway volumes is freight, resulting in damaged streets
In order to address these challenges, the city proposed several solutions that fall into the following categories:
• Deployment of connected autonomous vehicles • Infrastructure improvement • Move Tucson Smartly campaign • Transportation data collection and management
The proposed solutions include:
• Bicycle sharing • Connected fire trucks and ambulances
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• Connected buses • Connected bus stops • Travel smart-phone apps • Advanced traffic controllers • Sensor equipped intelligent infrastructure
In addition to these desired areas of focus for the future, Tucson has implemented the following applications as listed in the successive sections (Figure 2.9 and Figure 2.10).
Figure 2.9 Smart city challenge: Tucson, AZ vision statement (City of Tucson, 2016)
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Figure 2.10 Smart city challenge: Tucson, AZ vision statement (City of Tucson, 2016)
Tugo Bike Share In November of 2017, Tugo Bike Share was launched in Tucson. There are 36 stations and 330 bikes in the system. Bikes can be rented per day at a low cost, or yearly passes can be purchased. The bikes offer travelers an inexpensive way to commute, run errands, and explore the city (Tugo Bike Share, 2019). AMORE Project The Adaptive Mobility with Reliability and Efficiency (AMORE) project, funded by the Federal Transit Administration’s Mobility-on-Demand Sandbox program, commenced in 2017. Metropia’s Driving Up Occupancy (DUO) carpooling feature and RubyRide’s service will increase transit ridership by providing better first-mile last-mile connectivity solutions.
2.1.9 Tempe, AZ The City of Tempe is pursuing a number of initiatives to make the city more livable and sustainable. Autonomous Vehicles The Technology and Innovation Steering Committee (TISC) established the Autonomous Vehicle (AV) Subcommittee to explore how AVs might impact the city and develop a plan for integrating
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AVs into the city fabric. The purpose of the City of Tempe TISC AV Subcommittee is to understand the current and possible future use of AVs in Tempe. The subcommittee is partnering with Arizona State University’s Center for Smart Cities and Regions to help facilitate conversation with AV companies, smart city experts and the public. The Center explored the potential future of AVs in Tempe and how AVs could support or provide challenges to achieving the Council’s strategic priorities, such as a 20-minute city, increased mobility through traffic reduction, increased access for people with disabilities or increased safety through a reduction of fatal and serious car crashes. The study resulted in the preparation of a report that documents the opportunities and risks associated with deploying AVs in the City of Tempe. The report recommended that the city develop an AV or smart mobility playbook. An AV or Smart Mobility Playbook would provide guidance to both city staff and industry as they increasingly engage on AV deployment, pilot projects, and training. Vision Zero Action Plan In February of 2019, Tempe was officially recognized as the first Vision Zero city in Arizona. The Vision Zero Action Plan of Tempe was approved in May of 2019, and it outlined how Tempe planned to reduce fatalities on roadways and intersections. The strategies proposed include outreach educational campaigns and changes to existing signals. Specific tactics include (City of Tempe, 2019c):
• Improving data sharing between the Police Department and the Transportation department by using electronic crash reporting software (example: TRACS) • Neighborhood traffic calming • Converting all city street lights to LED • Planning for autonomous vehicles The vision zero highlights of City of Tempe are illustrated in Figure 2.11.
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Figure 2.11 City of Tempe: vision zero (City of Tempe, 2019c)
Tempe Smart Government Initiatives Tempe City Council has set Strategic Priorities (City of Tempe, 2019b), which are overarching goals that are important to our City: creating a safe and secure community, quality of life, sustainable development and more. The City also established a Technology and Innovation Steering Committee, consisting of directors, deputy directors, the City’s Chief Operating Officer, and the City’s Chief Financial Officer. The committee’s purpose is to ensure Tempe’s investment in technology and information technology is collaborative, reflects a common vision of service delivery, and is operationally sustainable. As part of the subcommittee’s initiatives, a transparency website on the City’s Strategic Plan (City of Tempe, 2019a) is available to residents to see how the strategic priorities are being met. These five priorities are:
• Safe and Secure Communities • Strong Community Connections • Quality of Life • Sustainable Growth and Development • Financial Stability and Vitality
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Within each priority, between 20 and 30 performance measures are available for review. In addition to the five priorities, ten crosscutting themes have been identified to identify group and report performance measures in areas such as saving lives; advancing a multi-modal mobile city; upholding fairness, justice, inclusivity; building a growing, vibrant, community; engaging and empowering community members; producing positive outcomes for youth; fostering safety, education, well-being; advancing environmental stewardship; delivering helpful customer experiences; and driving economic vitality. By illustrating these crosscutting themes, efficiencies can be realized across City departments and technologies pooled to improve upon performance measures.
2.1.10 Florence Town of Florence has contracted with Milandr, Inc. of Denver, Colorado to build and operate a carrier-grade, commercial Smart City/Internet of Things (IoT) Network using the globally- adopted open standard LoRaWAN technology. One of the project is to deploy advanced water metering infrastructure with auto-read technology on a non-proprietary system. The communications network is also able to support SCADA, emergency services, and the Town’s departmental applications.
2.1.11 Belmont In 2017 Cascade Investment LLC, a firm owned by Bill Gates, invested $80 million to develop a planned smart city named Belmont in Arizona. The firm purchased 25,000 acres of undeveloped land 45 minutes west of Phoenix in the West Valley. This is a strategic move because the location of Belmont will be close to the proposed I-11 freeway, connecting the area to Las Vegas. The area also receives ample sunlight, making it a great location for solar power. It is planned that the 25,000 acres of land will be divided accordingly: 3,800 acres dedicated to office, retail, and commercial space; 470 dedicated for public schools; and the remaining space for 80,000 residential units. Belmont is projected to be similar in size and population to Tempe, Arizona. The following proposed technologies will be make Belmont an advanced smart city (Weiner, 2017):
• Connected infrastructure • High-speed digital networks • Data centers • Autonomous vehicles • Improved manufacturing and distributing technologies Figure 2.12 shows the approximated location of Belmont.
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Figure 2.12 Approximate location of Belmont (Weiner, 2017)
2.1.12 Flagstaff City Bike Share Pilot Program In 2018, the City of Flagstaff completed a six-month bike-share pilot program with Spin to see how successful bike-sharing would be in the Flagstaff community (Figure 2.13). Flagstaff worked jointly with Spin to deploy 300 bicycles throughout the city. Citizens used the Spin app to locate and rent nearby bicycles. The bicycles were available for $1 per hour, with a 50% discount for Northern Arizona University (NAU) students with a valid NAU email. Over the six-month period a total of 10,619 trips were recorded and 13,125 miles were traveled. This produced a 14438 lb. greenhouse gas reduction and provided citizens with a healthy alternative to driving. The City of Flagstaff views the pilot program as a success and the data generated from the program could be used to provide permanent bike share options for the community in the future (City of Flagstaff, 2019; Corina, 2018; Skabelund, 2018).
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Figure 2.13 Bike share in city of Flagstaff (Skabelund, 2018)
2.1.13 Maricopa County AZTech Led by the Maricopa County Department of Transportation and Arizona Department of Transportation, AZTech is a regional traffic management partnership in the Phoenix Metropolitan area that guides the application of Intelligent Transportation System (ITS) technologies for managing regional traffic. It carefully integrates individual traffic management strategies and technologies for the region's benefit while preserving operational control protocols important to individual jurisdictions. AZTech is serving as a coordinating entity for many different initiatives and technologies deployed in the region, including but not limited to (AZTech, 2019a):
1. Integrated corridor management (ICM): 2. Bell road adaptive signal control technology (ASCT) 3. Arterial smarter work zones concept (Kimley Horn, 2016) 4. AZTech smart corridors (AZTech, 2019c) 5. Collaborative incident management (AZTech, 2019d) 6. AZTech regional information system (ARIS) (AzTech, 2019b) 7. Regional archive data system (RADS)(AZTech, 2019f) 8. Connected vehicles (AZTech, 2019e)
A few initiatives are described below for illustrative purposes.
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• MCDOT SMART corridors In order to improve the efficiency and safety of its transportation system, MCDOT implemented the SMART (Systematically Managed Arterials) corridor program. This program is responsible for the deployment of advanced traffic controllers, improved signal timing strategies, and a fiber communications backbone along several of the regional corridors of Maricopa County (MCDOT, 2019b; Saleem & Head, 2017).
• MCDOT SMARTDrive Program Initiated in 2007, the MCDOT SMARTDrive Program focuses on improving the efficiency and safety of first responders at traffic intersections through the use of dedicated short-range communications (DSRC) technologies. DSRC allows for communication between roadway infrastructure and vehicles, preventing first responders from colliding at intersections by assigning right of way (MCDOT, 2019b; Saleem & Head, 2017).
• Anthem Connected Vehicle Test Bed Constructed in 2011, the Anthem connected vehicle test bed is composed of 5.3 miles of arterials and it serves as a data collecting station and a testing ground for new transportation technologies. The eleven signalized intersections in the test bed are equipped with DSRC radios, as are the emergency response vehicles so that they can communicate. A pedestrian crosswalk smartphone app was also developed to assist pedestrians with crossing at the signalized intersections. The site also tests new multimodal intelligent traffic signal systems (MMITSS). Figure 2.14 illustrates a connected fire truck and some of the associated infrastructure at this site (MCDOT, 2019b; Saleem & Head, 2017). Figure 2.15 shows an implemented DSRC sensor.
Figure 2.14 Connected fire truck (MCDOT, 2019b)
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Figure 2.15 DSRC sensor
• Bell Road Adaptive Signals In order to improve the efficiency of Bell Road, MCDOT installed adaptive signal control technology (ASCT) systems at 50 signalized intersections along the roadway (Figure 2.16). ASCT systems use sensors to collect data on traffic conditions. These new adaptive systems will adjust and optimize signal timing automatically to address changing traffic demands. This project was completed in 2018 (MCDOT, 2019a).
Figure 2.16 Bell Road adaptive signals (MCDOT, 2019a)
2.2 Statewide Technology Deployment
In addition to various jurisdictions undertaking a number of initiatives as described above, the state of Arizona is embracing technology on a statewide level to enhance connectivity, quality of life, and economic prosperity. A couple of illustrative key technologies that are transforming the state are discussed below (Coppola, 2016; Roadsbridge, 2011).
2.2.1 Wrong Way Detection ADOT has recently deployed a Wrong Way Driver detection and warning system. The pilot system is being designed to detect, alert and track wrong-way drivers using the following processes:
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• It will combine detection systems at freeway exit ramps, on the freeway and on freeway- to-freeway ramps to alert law enforcement and ADOT traffic operators and keep them apprised of the vehicle’s location. • At exit ramps, flashing LED warning signs will attempt to get the wrong-way driver to self-correct, while the system will activate alerts on overhead message boards and automatically turn traffic cameras toward the wrong-way vehicle to help ADOT operators track it. • Thermal sensor cameras will be used to detect the wrong-way vehicle on the mainline freeway and update its location for law enforcement officers and traffic operators.
2.2.2 Unmanned Aerial Vehicles (UAV or Drones) The Arizona Department of Transportation is also adding drones to help its engineering staff safely and more efficiently inspect hard-to-reach areas on some bridges and perform surveying work along state highways. Through a federal innovative technology grant, ADOT has eight new aerial drones that will be part of the agency’s mission to enhance safety and efficiency while shortening highway project delivery time
2.2.3 Ramp Meters Ramp meters are on-ramp signals that control the volume of vehicles entering a freeway in order to optimize freeway speeds and improve vehicle merging. Ramp meters rely on intelligent transportation systems to determine their timing and location and are currently in use on a number of valley freeway entrance ramps (ADOT, 2019b).
2.2.4 Bluetooth and Wi-Fi Vehicle Tracking Arizona cities are using Bluetooth and Wi-Fi signals produced by cars to track traffic and identify patterns. The cities of Mesa, Tempe, and Gilbert planned to deploy 130 traffic monitors into their transportation systems in 2018. The cities can use the information gathered from the sensors to identify problems in traffic flow and to warm users of congested arterials. The City of Chandler already uses this technology to improve its traffic flow, using the information to predict and display travel times for drivers, and to warn drivers of congested traffic conditions (Coppola, 2016; Roadsbridge, 2011)
2.2.5 Self-Driving Vehicles Waymo Waymo has been testing its self-driving cars in the Phoenix area since 2016. All the vans are piloted by a driver in case of emergencies, and Waymo uses Arizona’s relaxed automated vehicle laws to test and improve their driverless technology (Reuters, 2018). An autonomous Waymo vehicle in Arizona is depicted in Figure 2.17.
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Figure 2.17 Waymo autonomous vehicle in Arizona (Cnet, 2019)
Semi-Trucks Waymo announced in May 2019 that they would test their self-driving Semi Trucks (Figure 2.18) on the highways and freeways of Phoenix (Cnet, 2019).
Figure 2.18 Waymo autonomous truck (Cnet, 2019)
TuSimple is another company that is testing autonomous trucks on the state’s freeways including I-10 and I-17 corridors.
Nikola manufacturers zero-emission trucks. These are hydrogen-electric trucks that emit no pollutants. Nikola is setting up a manufacturing plant in Coolidge, Arizona and will begin production in 2022 (Wiles, 2019).
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2.3 Micromobility in Cities
A number of cities have begun to address the challenges presented by micromobility modes such as e-scooters, e-bikes, and potentially slow-moving self-driving shuttles in the future (such as the Olli by Local Motors). Some of the key challenges include the sheer number of e-scooters that crowd sidewalks and streets, and the improper parking and placement of the e-scooters.
The City of Chandler is considering allowing e-scooter and bike-sharing in the city. They are doing surveys to gather user opinion over e-scooters and bike-sharing services operating in cities across the country (City of Chandler, 2019b). The City of Gilbert is assembling a document (Figure 2.19) to show enforcement strategies and legal requirements for all micro mobility modes (City of Gilbert, 2019).
Figure 2.19 Micro mobility type of transportation in city of Gilbert (City of Gilbert, 2019)
The City of Glendale is ensuring that micromobility modes do not affect quality of life in the city. City leaders had sent a cease-and-desist letter to Bird Rides, Inc., a dockless scooter-share company, demanding that all of their scooters in Glendale be picked up and taken away (January 2019) (Barry, 2019).
The City of Scottsdale passed new rules in 2018 for the usage of e-scooter and motorized bikes (Azfamily, 2018):
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• Drivers are prohibited from riding electric bikes and scooters while under the influence of alcohol. • Allowed on sidewalks, but drivers must obey traffic laws and yield to pedestrians. • Keep sidewalks open for pedestrians. • The owner is required to keep devices properly parked. • Devices should be operable and used. • Do not park too many devices together. • Respect private property.
2.4 Demonstrations of Automated Micromobility in the Valley
Arizona has become a testbed for a number of pilot demonstrations of automated micromobility. While many cities now have e-scooters and e-bikes (in sharing mode) deployed for facilitating movement of people, a few automated systems have been deployed in the region as well. These include:
Local Motors, based in Chandler, develops and builds the Olli through a novel 3D printing process. As part of a recent challenge, The East Valley Institute of Technology campus in Mesa won a bid for deployment of the autonomous shuttle Olli on its campus (Figure 2.20).
Figure 2.20 Olli Automated shuttle by local motors (Bhuiya, 2016)
Nuro partnered with Fry’s grocery stores to delivery groceries to households in the Scottsdale area. This pilot program ended in March 2019, following a successful conclusion of the 9-month
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pilot demonstration in which 2,000 grocery deliveries were performed by Nuro automated shuttles (Figure 2.21).
Figure 2.21 Nuro Grocery delivery shuttle (Russ Wiles, 2019)
2.5 Smart Street Lighting
A number of cities in Arizona are moving towards the deployment of smart street lighting.
2.5.1 Yuma Yuma is in a 25-year contract with anyCOMM Holdings that allows anyCOMM to use the city as a testing site for smart city technologies. A smart street lights project was initiated in 2016, and the goal of the project is to replace the city’s existing street lights with energy efficient LED lights capable of light control, and to equip the lights with nodes capable of Wi-Fi, video recording, and audio recording. The new lights will cut the city’s lighting bill by 50%, and the lighting control feature has the potential to cut energy costs by an additional 20%. The Wi-Fi and video and audio recordings will allow the city to provide reliable Internet to underserved communities and will provide data on traffic patterns. The project is predicted to be completed sometime in 2019 (City of Yuma, 2019). Figure 2.22 illustrates the Yuma smart lighting system.
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Figure 2.22 Yuma smart lighting (City of Yuma, 2019)
2.5.2 Mesa The city of Mesa is using energy-efficient LED streetlights. These lights will decrease the carbon footprint and provide good quality lighting through smart light-sensing that turns the light on at dusk and off at dawn (City of Mesa, 2019b).
2.5.3 Phoenix The city is replacing approximately 100,000 existing street light fixtures with energy-efficient light-emitting diode (LED) fixtures. The city estimates it will achieve a total net savings of approximately $22 million through 2030. The citywide conversion is programmed to be completed Fall 2019 (City of Phoenix, 2019b).
2.5.4 Flagstaff The world’s first International Dark Sky City, in 2018, the "Street Lighting for Dark Skies" program was initiated. Five different types of light-emitting diode, or LED, lights in neighborhoods around town were installed. The lights beam down onto streets and sidewalks, not up into the sky, protecting the night sky from unwanted glare (Associated Press, 2018).
2.5.5 Arizona Department of Transportation As part of the pilot program started in 2017, ADOT intends to convert 36 light fixtures located along the Loop 202 (Santan Freeway) from High-Pressure Sodium (HPS) to Light Emitting Diode (LED) (ADOT, 2019a).
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3 Smart Mobility
In order to reduce congestion and serve a growing population, smart technologies are being utilized to make transportation more efficient and enhance mobility for all. New sensors, applications, mobility options and services, and management/information systems are being deployed to decrease delay, enhance mobility and access to goods and services, and reduce emissions. This section will explore some of the new developments in the smart transportation domain. While it is possible to draw a distinction between smart transportation (which focuses on the systems) and smart mobility (which focuses on the users), these terms will be used interchangeably throughout this document. In the end, smart transportation systems are intended to enhance mobility and create smarter travelers; hence this document takes a more integrated and holistic perspective on the notions of smart transportation and smart mobility. Because MAG is the regional Metropolitan Planning Organization (MPO) for the valley, transportation is a major focus area of MAG’s work. For this reason, smart mobility/transportation applications are covered exclusively in this dedicated chapter.
3.1 Intelligent Transportation Systems (ITS)
Intelligent Transportation Systems, or ITS, involve the application of advanced sensors, surveillance cameras, computers, electronics and wired and wireless communication technologies in an integrated manner, along with effective management strategies, to improve safety, efficiency and reliability of all modes of the surface transportation system.
3.1.1 Traffic Management System Freeway Management The objectives of the freeway management system are to:
• Reduce the impacts and occurrence of recurring congestions on the freeway system; • Minimize the duration and effect of nonrecurring congestion (e.g., incident) on the freeway system; • Maximize the operational safety and efficiency of the traveling public; • Provide users with information necessary to aid them in making their trip decisions; • Provide a means of assisting users who have encountered problems (crashes, breakdown, etc.)
Modern freeway management systems typically include a central traffic management facility that serves as the nerve center of the freeway operations, employing the following technologies and services:
• Transportation Operations Center (TOC) is a dedicated facility to provide 24/7 freeway management operations. A TOC typically houses the computer equipment that controls
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the ITS field devices and a situation awareness room with a video wall, computer consoles, and trained traffic operations personnel. • Closed-Circuit Television (CCTV) cameras are essential for monitoring freeway conditions; • Ramp meters are used to regulate the volume of traffic entering the freeway to reduce congestion and improve safety. The advanced form of ramp meters is called adaptive ramp meters which automatically changes the metering intervals based on freeway main-line conditions. • Dynamic Message Signs (DMS) are used to provide advisory (incidents, constructions, travel times, amber/silver alerts, and public service announcements, etc.) to the travelers; • Vehicle detectors are installed on urban freeways at close spacing (e.g., every one mile) that provide real-time lane-by-lane traffic condition (e.g., volume, speed, etc.). These data are essential in managing freeway operations and supporting planning, operational analysis, and performance report; • Communications system is essential in supporting the operations of the field ITS devices. For example, In Phoenix area, ADOT implemented an extensive fiber optic communications network along major urban freeway corridors to allow the central management of the CCTV cameras, ramp meters, Dynamic Message Signs, and vehicle detectors from the Traffic Operations Center. • Traffic Incident Management (TIM) is a practice that requires close coordination between the incident responders and traffic operations. Incident responders are trained to leverage the transportation resources (CCTV imagery, messaging on the sign, lane closure barricades, etc.) with improved procedures that aim to reduce the traffic delay and improve safety during incident management. Recently, ADOT allowed the DPS officer to co-locate in the ADOT Traffic Operations Center that yielded a significant improvement in the Traffic Incident Management operations. • Freeway Service Patrol (FSP) Program is an important regional strategy that supports safe and efficient management and operation of the freeway system. The many services provided by the FSP include: (1) removing road debris and abandoned vehicles, (2) helping change tires, (3) providing emergency gasoline, and (4) transporting stranded motorist off the freeway system as soon as possible. In Arizona, the program is extremely popular with the traveling public, with an average of 14,000 stranded motorists helped annually. Arterial Management System The responsibility for management and operation of the arterial street system is based on jurisdictional boundaries and facility ownership. Every local agency owns and operates the agency’s traffic signals and related management systems with a few exceptions such as arterial traffic signals at freeway traffic interchanges, where the signals are owned by State DOT but may be operated by the local agency through an Inter-Governmental Agreement (IGA).
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Most of the larger cities have centralized traffic signal management systems, which are managed and operated from that jurisdiction’s Traffic Management Center (TMC). Communication from TMC to traffic signals is essential for monitoring the traffic signal status and modifying traffic signal timing for an intersection. The centralized traffic signal management system also coordinates the beginning of green phase to provide progression to minimize stops at traffic signals as vehicles traverse through a corridor.
The majority (98%) of the traffic signals in the US are operated based on time-of-day plans. That is, the duration of signal phases (i.e., red, yellow, and green) is pre-programmed based on observed traffic patterns. For example, a traffic signal might operate on different “timing plans” for the morning, mid-day, and evening periods to accommodate different commute scenarios. The time-of-day signal operations work reasonably well where an area’s activity pattern stays relatively constant.
Traffic detectors are used to improve the efficiency of the pre-programmed signal operation. For example, left-turn detection is commonly used to detect the presence of left-turn vehicles. If there is no vehicle in the left-turn lane, the left-turn green time can be re-allocated to the rest of the phases, which in turn minimizes the delay of other approaches.
Adaptive Traffic Signal Control (ATSC) is an advanced form of traffic signal operation which deploys traffic detectors at all approaches, at stop bar and upstream locations, to dynamically control traffic signal operations based on the actual traffic demands. ATSC relies on extensive traffic detection which is cost-prohibitive and imposes a maintenance challenge for large-scale deployment. ATSC is most suitable for special events and areas experiencing dynamic traffic patterns.
Emergency Vehicle Preemption (EVP) is an important feature of the traffic signal system that provides right-of-way to an approaching emergency response vehicle while stopping traffic from conflicting approaches. EVP has been proven effective in cutting the emergency response time and facilitating the safe passage of emergency vehicles at the signalized intersections. An EVP system is typically comprised of a device mounted in the emergency vehicle that sends a request for traffic signal priority, and the receivers mounted on the traffic signal mast arms and electronics in the traffic signal cabinets that relay the request to the signal controller for providing the preemption service.
Broadcast of traffic signal information directly from intersection to vehicles is being experimented as part of the Connected Vehicle development. A national standard of traffic signal timing information format called Signal Phase and Timing (SPaT) has been created as part of the Connected Vehicle. The SPaT message can be broadcasted via the Connected Vehicle Dedicated Short Range Radio (DSRC) or through the centralized traffic signal management system to private sector system and distributed over cellular network. This application holds
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great potential in enhancing how the autonomous vehicle operates which is relying on the camera to “see” the traffic signal phasing as human do.
Figure 3.1 Illustration of Broadcasting Traffic Signal Information to Vehicles
Integrated Corridor Management Integrated Corridor Management (ICM) is the latest concept championed by the USDOT that aims to integrate traffic operations between freeways and adjacent arterials through institutional collaboration and proactive integration of existing infrastructure along major corridors. Two national pilot projects, Dallas and San Diego, were conducted to implement the ICM concept. These pilots successfully demonstrated the use of a Decision Support System (DSS) and modeling tools to identify the best solutions in managing the traffic on freeways and adjacent arterials during incidents. The ICM solutions include the use of freeway ITS assets to safely and efficiently divert traffic and suggest or automatically implement strategies to remedy the surge of traffic on the adjacent arterials. Where applicable, the solutions also include real-time coordination with transit services in the affected area.
ADOT, in association with MCDOT, recently received a federal grant through the Advanced Transportation Congestion Management Technology Demonstration program to implement ICM along the State Route 101L (Loop 101) that connects residents and tourists to key event centers, educational institutions, and all interstate corridors in the Phoenix metro area. The Loop
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101 mobility project includes the implementation of a Decision Support System, Adaptive Traffic Signal Control (ATSC), Connected Vehicle applications for transit and incident response vehicles, adaptive ramp metering, and an integrated traveler mobility application.
3.1.2 Transit ITS Advanced Public Transportation Systems (APTS) are defined as advanced technology-based ITS applications in public transportation. These applications are relevant to the fixed-route bus, paratransit, vanpool, and rail. These technologies can be used to improve passenger convenience, vehicle operations, and mechanical systems. Passenger convenience technologies directly benefit passengers through advanced traveler information, real-time schedule updates, and fare payment. Vehicle operations technologies are associated with dispatching vehicles and in-vehicle systems. Mechanical systems technologies are designed to remotely monitor the electrical and mechanical infrastructure of transit vehicles.
3.1.3 Advanced Traveler Information System The Advanced Traveler Information System provides real-time information on traffic conditions to the traveling public to aid their pre-trip and en-route decisions. Government traveler information services are typically provided via Dynamic Message Signs, 511 interactive telephone system, and state-wide 511 traveler information website.
Typical traveler information provided on the Dynamic Message Signs includes point-to-point travel time based on data reported by the freeway detectors, road weather condition, incidents, construction information, and general travel advisory. 511 is the Federal Communications Commission's designated nationwide three-digit telephone number for traveler information. Established in 1999, information provided by state DOT operated 511 telephone services varies widely by provider, by the information provided and by method of delivering the information. 511 traveler information websites are operated by the state DOT throughout the US. The 511 websites typically provide traffic condition reported by agency-owned traffic detectors, incident reports, construction events, and in some cases, transit services. In recent years, third-party traffic condition data (e.g., Google, Inrix, HERE, WAZE, etc.) are being included in the 511 traveler information service.
3.2 Ride Sharing and Ride Hailing Systems
In order to provide on-demand mobility-as-a-service, several different ride-hailing options have emerged in the marketplace. Ride-hailing services (also referred to as ride-sharing services, even though the rides often include only one passenger) have the potential to yield environmental, economic, and social benefits by enhancing ride-sharing and reducing the need for parking of private vehicles (Sheng, 2014). True ride-sharing systems will allow people to find others with similar commute routes and destinations to make travel as efficient as possible. This will reduce the amount of emissions produced by vehicle travel. One example of a ride-sharing app in the
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United States is Waze. Waze is a navigation and ride-sharing platform owned by Google that hopes to reduce the amount of congestion in the United States by making carpooling more convenient and accessible (Kyle Wiggers, 2018). Another ride-sharing system example is Dynamic Route OptimizationTM platform. This platform is a fully automated route optimization system that automatically creates the most efficient delivery and or pick-up routes in real time for freight transportation. The software analyzes large quantities of map data to choose the optimal route, reducing the energy needed to travel (Route4Me, 2019).
3.2.1 Mobility-as-a-service The key concept behind urban mobility-as-a-service (MaaS) is to offer travelers a mobility solution based on their needs. Table 3.4 provides examples of some new applications in the mobility-as-a-service space. Table 3.1 Examples of Mobility-as-a-Service Mobility-as-a-Service Description Uber and Lyft Uber and Lyft are the most popular ride-hailing services available in the marketplace. Both services provide on-demand rides that generally cost less than that charged by traditional taxi companies. Riders can track their rides on the smartphone app and make payment through the app as well. Both Uber and Lyft offer ride- sharing capabilities in select markets; they have also formed partnerships with transit agencies to facilitate first-mile/last-mile connectivity. Optimile This application offers a large variety of travel options so that citizens can plan their trips through public transportation in a single, smartphone application. This platform also allows travelers to pay for their travel mode through the app (Optimile, 2019). Moovit This application combines information from public transit operators and authorities. Moovit is an application available in Android and iOS that provides travelers a real-time traffic picture, and the best route for the trip. Moovit collects up to five billion anonymous data points daily (Moovit, 2019). Wunder Mobility Wunder Mobility is a mobility-as-a-service platform for carpool, shuttle, and fleet. The carpool technology connects the passengers with drivers traveling in a similar direction. The shuttle technology will enable the users to launch their own branded shuttle service. Moreover, the fleet technology Provides software and hardware to help the users to launch their free-floating sharing business (Wunder Mobility, 2019)
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3.3 Connected and Autonomous Vehicles
Connected and autonomous vehicles (CAV) are under development and are viewed as the future of transportation systems. Human-driven vehicular traffic streams experience traffic waves due to the acceleration, deceleration, and speed variability caused by drivers’ behavior. Fully automated, autonomous, or “self-driving” vehicles are defined by the U.S. Department of Transportation's National Highway Traffic Safety Administration (NHTSA) as “those in which operation of the vehicle occurs without direct driver input to control the steering, acceleration, and braking and are designed so that the driver is not expected to constantly monitor the roadway while operating in self-driving mode”. NHTSA adapted the Society of Automotive Engineers definitions and classified the level of automation into five levels (NHTSA, 2018):
• Level 0: Human drivers perform all functions in navigating and controlling the vehicle • Level 1: Human drivers with an advanced driver assist system • Level 2: Advanced driver assist system (ADAS) able to control both steering and brakes (human drivers need to pay full attention) • Level 3: An automated driving system (ADS) that can operate the vehicle fully under some circumstances (The human driver must be ready to take back control at any time that the ADS needs the driver to do so). • Level 4: ADS operate the vehicle and perform all driving tasks. Human drivers are still in the vehicle, positioned in the driver seat. • Level 5: Driverless (the human occupants act only as a passenger, and the ADS operates the car entirely).
Many auto manufacturers and technology companies are developing and testing these vehicles. The leading companies in testing autonomous vehicles are (DeNisco-Rayome, 2018)
1. General Motors (GM) 2. Waymo 3. Daimler-Bosch 4. Ford 5. Volkswagen Group 6. BMW-Intel-FCA 7. Aptiv 8. Renault-Nissan-Mitsubishi Alliance
As with ride-hailing services, there is some concern that connected and automated vehicles (CAV) may lead to increased travel (induced traffic) and unintended consequences of growth in vehicle miles of travel and carbon footprint. It is therefore necessary to develop a sound strategy for the introduction of connected and autonomous vehicles, both from an engineering standpoint and a policy standpoint, to mitigate and minimize any unintended consequences
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while realizing the fully mobility and quality of life benefits that such technologies and mobility options provide.
3.3.1 Connected and Autonomous Vehicles (CAV) Data Platform Autonomous vehicles rely on an extensive network of data to perform safely. The innovations outlined in Table 3.5 cover the areas needed to operate autonomous vehicles safely. These areas include live digital maps, vision sensor technology, and advanced driver assistance systems. Table 3.2 CAV Data Platform Examples Connected Autonomous Vehicle Description Innovation HERE HD Live Map An adaptive map that provides vehicles with all the information they need to operate autonomously. This information includes speed limits and road closures (HERE, 2019) EyeQ by Mobileye Vision technology used by autonomous vehicles to sense other vehicles sharing the roadway (Mobileye, 2018). Advanced Driver Assistance Systems Technology that can alert the driver to objects in the roadway and can also provide updated maps and route planning (NVIDIA, 2019).
Vehicle to vehicle (V2V) and vehicle to infrastructure (V2I) technologies allow vehicles to share information wirelessly so that drivers and traffic engineers are more aware of road, safety, and environmental conditions. Bluetooth equipped devices and vehicles make data sharing convenient and accessible. This data exchange makes connected autonomous vehicles possible (ITS, 2019). The advent of 5G connectivity is likely to greatly advance the ability to connect vehicles and travelers, and transmit information and signals at much higher speeds than today, thus eliminating any latency in message transmission and response times.
3.4 Smart Parking
Smart parking reduces emissions by decreasing the time a vehicle has to travel to find a parking space. New advances in this field include applications that guide users to the nearest available spot, sensors that monitor spot occupation, and displays in parking garages that show how many spots are available in each section. Table 3.6 presents recent advances in smart parking applications. The new advances in smart parking applications.
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Table 3.3 Smart Parking Applications Smart Parking Application Description ParkAdmin An integrative software that allows for the complete monitoring of parking facilities. It tracks vehicle plates and keeps track of permanent and temporary parking permits (Operations Commander, 2019). Venire Parking Management Parking management kiosk that monitors vehicle volumes System and includes automatic paying options (Aventura Technologies, 2019). CUR Systemtechnik Parking guidance system provider that includes single space detection, car counting, and LED space availability display applications (Cur-Systemtechni, 2019).
3.5 Wireless Signal Tracking
Vehicle Bluetooth and Wi-Fi signals are being used to track travel time and origin-destination (OD) pattern. Sensors strategically placed approximately 0.5 to 1 mile apart along roadways identify repeated MAC addresses produced by the vehicles themselves or by devices within the vehicles. This information is used to calculate the time required for vehicles to travel between sensor zones. Traffic engineers use this information to alert drivers of congestion and to identify areas where delays occur. In Arizona, a number of cities have tested and employed Bluetooth and Wi-Fi traffic monitoring systems, and they have proved to be an inexpensive method for alerting drivers of roadway conditions (Federal Highway Administration , 2019).
Bluetooth is also being used to generate origin-destination (OD) data. This information can be used by traffic professionals to identify OD trip patterns; and it is less expensive than traditional license plate matching and manual car following OD data collection methods. The Australian Department of Transport and Main Roads has tested Bluetooth origin-destination data collection and compared it to traditional methods. They found that tracking vehicles through their MAC addresses performed as well as other methods at a much lower cost, but that improvements were needed in signal capture rates and station set-up methods (Blogg, Semler, Hingorani, & Troutbeck, 2010).
Another innovative wireless signal tracking source is Tire Pressure Monitoring Systems (TPMS) sensor signals emitted from passing vehicles. MAG conducted a pilot study deploying 12 Blyncsy sensors which are capable of picking up Wi-Fi, Bluetooth and TPMS sensors signals for collecting travel time and OD information. Initial results indicates TPMS sensors accounted for less than 5 percent of all the signal sources collected, possibly due to its low-energy, short-range nature. Table 3.7 illustrates examples of wireless signal tracking devices.
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Table 3.4 Examples of Wireless Signal Tracking Device
Wireless Signal Description Monitoring Device BTM BTM is a Bluetooth traffic monitoring system that tracks vehicle travel By TPA North times. Its attributes include: America Inc. • Easy Cabinet or pole device mounting • Ethernet, GPRS, HSPA, and LTE communication options • 125-meter signal detection range (TPA North America Inc., 2019)
Trafficbox Traffic box is a battery-operated Bluetooth and Wi-Fi sensor used to By Smats Traffic collect travel time information. Its attributes include: Solutions • Durable waterproof carrying case • Easy pole mounting design • Adjustable scanning range (Smatstraffic, 2019)
Blyncsy sensor Blyncsy sensor is capable of picking up three type of signal: Wi-Fi, By Blyncsy Bluetooth and TPMS (Tire Pressure Monitoring System).
3.6 Smart Bus Operations
Many transit agencies are implementing systems that provide travelers real-time information about locations of transit vehicles, travel times, transit vehicle occupancy levels, and time (at stop) when the next bus or rail vehicle will arrive. This information can be transmitted by equipping all transit vehicles with GPS devices that relay location information in real-time. GPS technology allows for transit users to pinpoint where buses are located at any time, making arrivals and departures easier to identify. The OneBusAway app is a good example of a traveler information system that leverages smart transit operations by turning data into actionable information for transit riders. Similarly, the City of Denver used GPS technologies to improve the efficiency and timing of its bus fleet.
3.7 Electronic Toll Collection
Electronic toll collection systems charge registered vehicles directly to their accounts so that they are not required to stop. The stations identify and charge registered vehicles using sensors in the roadway and video cameras equipped with license plate recognition. This reduces delays, congestion and air pollution. When compared to manual toll collection booths that require drivers to stop, ETC systems produce savings of approximately $135,000 per year per toll facility (Auer et al., 2016).
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3.8 Unmanned Aerial Systems or Vehicles (UAS or UAV)
Unmanned Aircraft Systems (UAS), also commonly referred to as Drones, constitute aircraft without a human pilot. In practice, the term UAS and UAV (Unmanned Aerial Vehicle) can be used interchangeably. The UAS is operated and monitored from the ground. The UAS is subject to Federal Aviation Administration regulation to ensure the safety of people and property on the ground. Since the growth in demand for UAS has grown in different areas, e.g., transportation, agriculture, photography, and package delivery, ensuring the safety of UAS has become one of the most challenging issues. It is predicted that in the next ten years, $93 billion will be spent on this and related technology worldwide. Unmanned aircraft, or drones, are being utilized to control avalanches and to inspect the safety and condition of different traffic infrastructure systems such as roadways and bridges (Irizarry & Johnson, 2014).
Drones are being used to monitor infrastructure, inspect bridges and other infrastructure elements particularly in hard-to-reach locations, and gather data about pavement conditions on a continuous basis. In addition, drones are being used to monitor traffic in real time, capture images, and provide data to traffic management centers for proactive real-time management of traffic congestion and communicating information to travelers. Drones are being considered for use to deliver packages (small packages), particularly with the growth of e-commerce and delivery-based services. More recently, Uber (Figure 3.1) and a few other companies have announced plans to explore passenger transport using automated flying vehicles. It is envisioned that automated mobility will increasingly explore the use of air space to overcome capacity limitations on the ground.
Figure 3.2 Concept of Uber Elevate (Uber, 2019)
UAVs provide state DOTs “eyes in the sky”. The states can benefit from UAVs during site construction in terms of safety of workers, accelerating construction processes, speeding up data
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collection, and asset maintenance. Each state has its pilot program to ensure the safe introduction of Unmanned Aircraft Systems in the airspace. In Arizona, the UAV is being used in transportation applications (monitoring the traffic safety), delivery of vital supplies (medicines) to remote areas, emergency management, and search and rescue missions (AZCommerce, 2019; Zipline, 2014). 3.9 Hyperloop
In the very early research, development and testing phase, Hyperloop (Figure 3.2) is a new mode of long-distance transportation that involves transporting people in small pods through vacuum tubes at very high speeds. Vacuum tubes may be constructed underground or over ground, but the vacuum tube technology essentially allows pods to be hurtled across long distances in short periods of time. Speeds of 600 mph or greater have been proposed for this technology. A few companies (such as Virgin Hyperloop One) have proposed building shorter distance prototypes in a few locations with a view to proving the viability of the technology in a real-world setting. Plans for initial prototypes exist for Dubai – Abu Dhabi, Mumbai – Pune (India), and Los Angeles – Las Vegas. A number of other locations are being explored in the United States, with a few involving connections to Phoenix.
Figure 3.3 A Rendering of the Hyperloop Transportation System (Hyperloop, 2019)
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3.10 Advanced Data Analytics
While much progress has been made in the development of new technologies and systems, similar progress has also been made in data science. Crowdsourced applications are allowing agencies to collect data across space and time from large numbers of agents using the system; this data can be mined to derive predictive analytics and proactively manage the system and optimize performance before issues occur. The information can also be relayed to the traveling public so that they are empowered to make informed decisions. A number of big data providers have emerged in the mobility space including HERE, Inrix, and AirSage, to name a few. These big data providers offer information about mobility patterns and transportation system usage and performance at a variety of spatial and temporal scales. This data can be analyzed to draw actionable information that can be utilized by the traveling public as well as traffic management centers. A number of companies are building cloud-based decision support systems for mobility to better manage traffic, parking, transit operations, emissions, and incident response.
4 Examples of Smart Transportation Applications
There are a number of examples that illustrate the deployment of smart transportation technologies and mobility options. Within the scope of this effort, it is impossible to provide a comprehensive review of these deployments and plans. This chapter offers brief descriptions of some examples, with a view to help inform technology deployment plans that MAG may wish to pursue.
Because smart transportation deployments are strongly inter-connected, it is somewhat difficult to organize the case studies along thematic lines. Examples have been classified and organized into themes based on the major emphasis of the technology deployment; however, it should be recognized that most deployments include multiple technologies and address a multitude of thematic areas.
4.1 Holistic Smart Transportation Deployment Initiatives
A number of areas have attempted to develop smart transportation plans that address multiple objectives and include a number of technologies and components. This section presents a few examples.
4.1.1 Jacksonville Urban Area Metropolitan Planning Organization (JUMPO) On June 30, 2017, North Florida released their Smart Region Master Plan which outlines how North Florida plans to implement and coordinate new smart technologies to improve the livability of the region (North Florida TPO, 2017). Figure 4.1 outlines the goals of the smart region master plan. In December 2017 the Jacksonville Transportation Authority (JTA) launched the Ultimate Urban Circulator (U2C) Autonomous Vehicle Test and Learn track, which will deploy
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an autonomous shuttle system into the city of Jacksonville. This project will allow the JTA to collect data that can be used to assess feasibility and effectiveness of implementing autonomous transit (Metro Magazine, 2019).
Figure 4.1 North Florida smart region plan framework (North Florida TPO, 2017)
4.1.2 Columbus, Ohio Columbus was the winner of the USDOT smart city challenge of 2015. Columbus proposed a suite of technologies and initiatives to create an integrated smart community. The challenges facing Columbus include high infant mortality rates in low-income communities due to limited access to medical facilities, outdated infrastructure, traffic congestion, and limited parking resources. Figure 4.2 outlines the goals of the Smart Columbus Plan (U.S. DOT, 2016a).
• Trip planning application • Universal payment system for all public transportation • Smartphone application specifically for citizens with disabilities • Integration of travel options at specific locations • Smart corridors • Smart traffic signals • Smart street lighting • Free public WiFi along routes • Autonomous vehicles
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Figure 4.2 City of Columbus goals (U.S. DOT, 2016a)
4.1.3 Denver, Colorado Individual communities in Denver are impacted by air pollution as well as noise pollution due to freight travel. In order to address this issue, Denver will implement new technologies to improve freight parking, freight signal optimization, and traffic information systems. The components of Denver’s Smart City Plan are outlined below in Figure 4.3 (City of Denver, 2016). The plan is a holistic initiative that integrates a number of components. These include the mobility-on- demand services, electrification of transportation to greatly increase the uptake of electric vehicles, and the connected and automated (or intelligent) vehicles. In addition, Denver will create an enterprise data management (EDM) platform that will help build integrated databases that can be mined for actionable information and keeping residents informed of real-time conditions.
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Figure 4.3 Denver's smart city program (City of Denver, 2016)
4.1.4 Portland, OR Portland, OR hopes to remove the barriers separating lower income communities from the resources they need to prosper through the use of new smart technologies. These technologies include LED street lights, smart traffic signals, free public Wi-Fi, electric charging stations, and an autonomous vehicle platform. By making public transportation more affordable and accessible, Portland, Oregon hopes to improve the economic conditions of under-served communities (City of Portland, 2016). The Portland Oregon Smart City Technology Hardware Foundation Diagram is illustrated in Figure 4.4. Once again, it can be seen that transportation is viewed as a fundamental infrastructure system that can enable access to opportunities and economic growth. By integrating a number of technologies with a comprehensive data platform, cities such as Portland, Oregon hope to empower residents with mobile access to services (anytime and anywhere) and usable real-time information that will help residents make informed decisions as they go about their daily lives.
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Figure 4.4 Oregon smart city technology foundation diagram (City of Portland, 2016)
4.2 Examples of Emerging Mobility Technologies – Shared, Automated, and Electric
The advent of connected and autonomous vehicle (CAV) technologies has inspired many jurisdictions, including a number of cities in Arizona, to initiative plans on how these technologies may be deployed and utilized in their communities. The introduction of 5G technology will make it possible to greatly enhance vehicle to vehicle (V2V) and vehicle to infrastructure (V2I) communications; connectivity at 5G speeds will also have a transformative influence on the ability of civic entities to integrate, mine, and communicate actionable data to stakeholders and residents. The examples in this section focus on connected and autonomous (or automated) vehicle deployment initiatives, although they do include other components of a smart transportation system as well. For instance, the Jacksonville MPO example that was presented earlier in Section 4.1 constitutes a holistic smart region plan, but includes a key connected and autonomous vehicle deployment component as part of the plan.
Another emerging mobility technology that has already found itself into the marketplace and continues to evolve on a daily basis is the ride-hailing platforms that not only transport people, but also transport goods and services to people. These companies, such as Uber and Lyft, aim to provide high-quality mobility-on-demand service and make it feasible for people to hail, share, track, and pay for rides through a convenient smartphone app. As these companies increasingly forge partnerships with auto manufacturers, the future may see ride-hailing companies deploying fleets of autonomous vehicles that can serve travel needs of communities at very low
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cost. If the vehicle fleets are largely electric (essentially leading to Shared Autonomous Electric Vehicles or SAEV), then the energy and emissions footprint of travel may go down – contributing to a cleaner and greener environment. Both Uber and Lyft have experienced dramatic growth in usage over the past several years and automation is seen as a key mechanism to scale the technology up to a level where it can serve daily travel demand for many residents – thus potentially drawing closer the day when private car ownership declines, and the cars that are owned privately are largely electric.
4.2.1 San Francisco, CA San Francisco has been experiencing growing levels of traffic congestion. The city is seeking to deploy smart technologies to alleviate traffic congestion, promote alternative mode use, and reduce the carbon footprint. These technologies include:
• Creating connected regional carpool lanes • Regional Carpooling System • Shared mobility options (car-share, bike-share, scooter-share, carpooling, taxis, and private transit) • Shared Electric Connected Automated Vehicles or SECAV (City of San Francisco, 2016)
The State of California at large has proven to be a major testing ground for autonomous vehicles. Much of this testing is happening in the San Francisco Bay Area and Silicon Valley. According to recent reports published by the California Department of Motor Vehicles, 62 companies have deployed a collective 678 autonomous cars as part of their research, development, and testing activities.
The critical outcomes desired for the City of San Francisco are outlined below in Table 4.1. Table 4.1 San Francisco Smart City Key Outcomes (City of San Francisco, 2016)
4.2.2 Pittsburgh, PA The City of Pittsburgh, PA hopes to address its air pollution and air quality issue by converting to electric power sources. This conversion will reduce transportation emissions by 50% from its current level. The Smart Pittsburgh plan includes converting 40,000 existing street light fixtures to LED light fixtures to reduce energy consumption, installing smart street lights equipped with
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sensors to monitor air quality, making electric vehicle charging stations more available, and converting the city’s fleet of public vehicles into electric powered vehicles to reduce emissions (Smart PGH, 2016).
Like cities in Arizona, Pittsburgh has become a testbed for autonomous vehicle operations. Carnegie Mellon University has been playing a key role in advancing automated vehicle technologies and has a number of vehicles being tested on Pittsburgh’s roads. Other companies that are testing automated vehicle technologies in Pittsburgh include Aptiv, Argo AI, Aurora Innovation, and Uber. According to reports filed by these companies, they are testing 55 driverless cars in 32 of Pittsburgh’s neighborhoods and suburbs. Most of the cars falls under the Society of Automotive Engineers (SAE) Level 4 designation, meaning that they’re capable of performing all driving functions autonomously under certain conditions and a human operator must be present in the vehicle at all times.
4.2.3 Las Vegas, NV In order to make itself as efficient and livable as possible, the City of Las Vegas is investing in smart city technology to enhance quality of life for its inhabitants. The city is seeking to leverage connectivity and automation to develop a smart city that is easy to navigate. To facilitate smart city technology infrastructure investment, Las Vegas City Council established the Innovation District in its urban core. Current projects underway include autonomous vehicle deployments, connected traffic corridors, and easily accessed open data applications.
Noteworthy developments include the nation’s first public self-driving shuttle pilot project, circulating a 0.6-mile loop in the Fremont East Entertainment District within the city’s Innovation District (Figure 4-5). Partnered and funded by AAA and Keolis, this pilot has provided free services to more than 30,000 people over the course of a year. Additionally, as a part of connected traffic corridors effort, the deployment of traffic signals equipped with Dedicated Short Range Communications (DSRC) radios offers a proving ground for the assessment of CAV’s vehicle-to-infrastructure communication capability. An array of IoT devices such as smart lightings, high definition video cameras, and sound and motion sensors have also been deployed in the Innovation District to help improve public safety and save energy (Las Vegas City Hall, 2019).
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Figure 4.5 Autonomous vehicle pilot test in Las Vegas (Las Vegas City Hall, 2019)
4.2.4 Atlanta, GA In September 2017, The City of Atlanta initiated the North Avenue Smart Corridor, a connected vehicle route that utilizes smart technology to optimize traffic flow and increase safety for both bicycle and pedestrian traffic. The new technologies include high definition video cameras that monitor the number of vehicles, vehicle speed, and vehicle occupant level; thermal cameras to sense pedestrians; and the TravelSafely smartphone application. All of these connected technologies have contributed to improved safety of the corridor, which has experienced 25% less crashes and an improved traffic flow rate since the corridor was converted into a smart and connected corridor (Diamond, 2018)
4.3 Data and Information Systems
Critical to the development of a smart region is the gathering real-time data in a multitude of domains, fusing such data in a manner that is consistent, and then mining the data to derive predictive analytics that can be used to monitor and optimize system performance, empower residents, and influence behavior. Many regions have enterprise data management systems as a key component of their smart region development plans. Using (big) data streams derived from a number of sources, cities are striving to derive useful analytics and employ data-driven approaches to decision-making, both in the long term and in the short term. Many of the examples described previously have integrated data platforms at the heart of their smart region development initiatives. Several additional examples are described in this section.
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4.3.1 Kansas City, MO Kansas City is using an array of sensors and other real-time data collection technologies to gather detailed traffic data and improve the quality of life for residents by providing real-time and predictive traffic information. This information is being used to understand, monitor, and optimize traffic flow, crashes, energy consumption, air pollution, and resident health. The Kansas City Smart City Vision can be seen below in Figure 4.5 (City of Kansas City, 2016).
Figure 4.6 Kansas smart city vision (City of Kansas City, 2016)
4.3.2 Chicago, IL Another area where data and information systems can play a key role in enhancing efficiency of system operations is “parking”. The city of Chicago utilizes the Parqex smartphone application to optimize parking system performance and enable residents to find parking spaces and be informed about costs in advance. Parqex can be used by drivers to find the nearest available spot, thus cutting down on the travel time required to find a suitable parking spot (Parqex, 2019). More broadly, the City of Chicago aims to become a connected smart city to improve the quality of life for its residents, visitors, and businesses. The broader smart city plan for Chicago involves installing sensors to monitor air quality, park lawn moisture content, and infrastructure to identify and address poor infrastructure conditions that warrant corrective action.
4.3.3 Salt Lake City, Utah Utah Department of Transportation is now partnering with Panasonic to build a “Smart Roadway” Data network. By enhancing the communication between vehicles and infrastructure,
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Panasonic will help the state to accommodate the huge wave of connected and autonomous vehicle to safely and efficiently operate in the state routes (UDOT, 2019).
4.4 Streets and Lighting
Smart transportation systems must inevitably address key components of the infrastructure including streets and lighting. Many cities and states are taking a fresh look at their streets and lighting systems with a view to make them smarter – and hence safer, more efficient, and more sustainable. A few examples are described in this section.
4.4.1 Florida The state of Florida has implemented a number of initiatives to transform itself into a smart enterprise. These plans include the Complete Streets Plan, the Ultimate Urban Circulator (U2C), and the Smart Region Master Plan. The Florida Department of Transportation implemented the Complete Streets Plan in 2015 to create a transportation network that could be used by all forms of travel and is user-friendly (FDOT, 2017). These new policies aim to provide a complete street network that can serve all forms of travel.
4.4.2 Illinois In 2017, the State of Illinois issued a Request for Proposal to establish a contract for Smart Street Lighting. They secured three vendors to provide smart lighting technologies. These vendors were Johnson Controls, Globetrotters Engineering, and TEN Connected Solutions. The technologies introduced included (Illinois DOT, 2019):
• LED light fixtures • Cheaper than traditional lighting, producing energy savings of 50% or more • Requires less maintenance than traditional lighting and has a longer life span • Better light quality • Central Management Systems • Remotely monitors light fixtures to adapt to different situations in real time, adjusting lighting based on the presence or absence of vehicles and emergencies • Provides maintenance alerts in real time. • Backhaul communications networks • Connects the luminaries to the central management system for data exchange • Field Control Devices • Enable light fixture control
These new technologies will improve functionality and efficiency. Figure 4.6 outlines how all these different smart technologies would interact.
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Figure 4.7 Smart street lighting framework (Illinois DOT, 2019)
4.4.3 San Diego, CA The City of San Diego is replacing its current street lights with efficient smart LED light fixtures as part of its smart city plans. These light fixtures will be equipped with sensors to collect data in real time on vehicle counts, parking information, temperature, pressure, and humidity. This information can be used by the city to improve transportation efficiency and pedestrian safety. The lights are also cost-effective and use less power than the older fixtures. Figure 4.7 below shows how these smart light fixtures operate (City of San Diego, 2019)
Figure 4.8 Operation of San Diego smart light fixtures (City of San Diego, 2019)
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5 Smart Technologies in Non-Transportation Domains
There are eight non-transportation application domains in which smart city technologies can make a significant difference to communities and overall quality of life in metropolitan areas. While the previous chapters focused exclusively on transportation applications, this chapter provides an overview of smart technologies in the other eight domains that fall within the scope of this report and often constitute elements of a comprehensive smart region plan.
5.1 Smart Health
5.1.1 Smart Health New health monitoring devices make it possible for patients to receive alerts when they are in need of medication or a health checkup. These monitors also supply physicians with up to date data on patient wellbeing and health, producing better diagnostic procedures and outcomes (Priyanshi, 2016).
Smart Technologies can also be leveraged to create an integrated platform for health services. This platform would be an application that combines all health services into one convenient and easy to use system. This system would have up to date information on patients, and information would be coordinated between patients and physicians (Priyanshi, 2016).
5.1.2 Smart Environment New technologies like advanced carbon monoxide detectors, low-temperature sensors, advanced fire alarms, and water sensors are creating smart home environments. These technologies alert homeowners of water leakages, high carbon monoxide levels, and low temperatures via their smartphones. This allows homeowners to respond to problems early before they become damaging (ProTech Security, 2018).
New wallpaper that acts as a fire alarm has been developed. This special wallpaper is composed of flame-resistant material that becomes electrically conductive when exposed to heat. It will create a smart environment that can detect fires early before they spread (Rich, 2018).
Unmanned aerial vehicles can be used for agriculture, environmental protection, public safety, and traffic flow control (Mohammed, Idries, Mohamed, Al-Jaroodi, & Jawhar, 2014). All of these domains can be improved to create a smarter environment.
Unmanned aerial vehicles can be used in several areas of agriculture. These areas include field and soil analysis, crop planting, crop spraying, crop monitoring, and irrigation. UAVs cut energy costs involved in crop planting and can be used to monitor field dryness so that fields are watered more efficiently (Mazur, 2016)
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5.1.3 Smart Living Green technologies like wind and solar power are necessary parts of smart cities. They are clean energy sources that produce less harmful pollution, like the smog that is detrimental to a city’s health, and promote smart living (Deloitte, 2019)
5.1.4 Connected Health Information Systems In order to make health records more accessible, Maricopa County introduced the Maricopa Integrated Health System, so that patients would have free access to their medical records (MIHS, 2019).
5.2 Smart Buildings
This section explores the different technologies that optimize the energy consumption of buildings and other fixtures.
5.2.1 Smart Buildings and Structures Buildings equipped with smart technologies boost sustainability, improve safety, and cut energy costs. There are a variety of new technologies being applied to buildings to achieve this goal, and they include: heating and cooling systems equipped with dynamic sensors, lighting level control, smart elevator systems, carbon monoxide sensors, and organized security systems.
5.2.2 Smart Irrigation Systems The goal of smart cities is to provide the best living experience for all of the city’s inhabitants. High-quality public space is a priority of any smart city. To achieve this goal, sophisticated irrigation systems have been developed that monitor the moisture content of soils and provide information when a certain area needs to be watered. This decreases water consumption and improves the efficiency of the irrigation system, while maintaining a high-quality green space. This sort of system has already been implemented in the City of Barcelona which has seen a 25% drop in water costs since the new water management systems were adopted (Figure 5.1) (Libelium, 2016).
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Figure 5.1 Barcelona smart Irrigation system example (Libelium, 2016)
5.2.3 Energy Management New Energy Management Systems can be installed into buildings or college campuses to monitor energy use to save on energy costs. These systems optimize energy consumption and make it possible to identify where energy is being wasted (Ramey, 2014).
5.3 Smart Governance
This section explores how smart city technologies can be applied to governance to improve the services and functioning of a city.
5.3.1 Smart Government Smart government is a government that takes advantage of smart technologies to connect citizens with all of the resources they need to fulfill their needs and civic duties, typically through the Internet (Parker, 2019).
5.3.2 Reduce Bureaucracy New smart technologies have the potential to reduce the amount of bureaucracy hindering efficient and user-friendly governmental services. These technologies help identify areas of
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wasteful or redundant bureaucracy and eliminate them (Innovatebusinessit, 2019), while enhancing the efficiency of other processes through automation and connectivity.
5.3.3 Online Transaction Online transactions are more sustainable and faster than traditional paper or physical transactions. They make transactions more efficient. Online transactions are becoming even more accessible with the emergence of e-wallets, which allow customers to store money in a safer and more convenient place (Gent, 2018).
5.3.4 Government Social Media The digital infrastructure of the United States Government can be made more open and transparent by leveraging social media platforms. New technologies and improved digital performance will decrease wait times, encourage citizen involvement and awareness in government functions, and make the government more transparent (Amber, 2017).
5.3.5 Smart Public Service In order to serve the growing population, governments are using smart technologies to gather information and provide easily accessible platforms for citizens to use to fulfill their needs (Lanast Consulting Ltd., 2017)
5.4 Smart Energy
Energy consumption and associated costs can be reduced using smart city technologies. New renewable energy sources and utilities equipped with usage sensors make it possible to monitor and reduce energy consumption.
5.4.1 Smart Energy New organic materials have been discovered for possible use as solar cells. This new material is translucent and can be used in glass window panes, allowing solar energy to become more widely used. This new material can be deployed with different colors and is more sustainable than traditional silicon-based solar cells (University of Erlangen-Nuremberg, 2016). Smart grid and smart meters is another type of smart energy advancement. The grid is a network of transmission lines, substations, transformers and more that transfer the electricity from the power plant to homes and business offices. The smart grid is two-way communication between the utility and customers, and the sensing systems along the transmission lines. Advancement of the Internet of Things will make energy grids more reliable and allow them to repair themselves through a system of sensors and advanced software. This will improve efficiency and reduce the amount of human intervention and repair that is ordinarily necessary. New technologies also allow meters to monitor and communicate the power usage of each house so that the utility companies can use the data to encourage people not to use energy during peak consumption hours (Deloitte, 2019).
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5.5 Smart Water Management
Smart water management is the process of using sensors to detect leakages and pollution in water systems. This section will describe new, emerging smart water management technologies.
5.5.1 Smart Water Management In order to conserve water for a growing population, smart technologies are applied to water systems for leakage detection. This will allow the municipality to fix water leakages quickly and reduce the amount of wasted water (Deloitte, 2019).
5.5.2 Smart Water Monitoring Agriculture accounts for more than 70% of the total water consumed, and smart technologies will monitor field dryness and slope in order to deliver the appropriate amount of water. This will improve the efficiency of agricultural systems, reduce the risk of overwatering crops, and reduce the total amount of water being used (Deloitte, 2019).
5.5.3 Smart Chemical Leakage Detection Any chemical leakages are dangerous to public health and to the environment. In order to identify and fix chemical leakages in a prompt manner, drones equipped with smart sensors analyze areas and scan for potential leaks (Rossi & Brunelli, 2015)
5.5.4 Smart Pollution Control In order to reduce the time between when pollutants are introduced to water systems and their detection, new smart sensors will monitor water quality constantly to catch pollutants as soon as they are introduced (Deloitte, 2019).
5.6 Smart Waste Management
Self-compacting trash containers, smart waste container volume sensors, and new waste management policies requiring citizens to clean and sort their trash into distinct categories are transforming traditional waste management into smart waste management methods. This section presents some of these new technologies.
5.6.1 Smart Waste Management Smart cities monitor waste by gathering information with sensors. Examples include the volume of waste in trash containers, what type of waste is being produced, and how much trash is being produced over time (Figure 5.2). This information is used to boost the efficiency of waste management systems (Aazam, St-Hilaire, Lung, & Lambadaris, 2016).
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Figure 5.2 Smart waste management system outline (Aazam et al., 2016)
5.6.2 Smart Garbage Disposal New technologies monitor trash as it accumulates and alerts the municipality when the bins are full. This boosts the efficiency of trash collection routes as trash collectors will only go to the bins that are recorded as full and not waste time emptying half-filled bins. It also prevents trash from overflowing out of the bins and polluting the environment (Yusof, Jidin, & Rahim, 2017). The outline of a smart garbage disposal process is illustrated in Figure 5.3.
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Figure 5.3 Outline of a smart garbage disposal process (Yusof et al., 2017)
5.6.3 Smart Trash Containers Smart trash containers monitor the level of the trash that accumulates and send this data to the municipality to alert them of trash collection time. Particular smart trash containers are also equipped with solar panels to make them self-compacting, allowing for more storage space. All of these qualities boost efficiency and cleanliness (Bigbelly, 2019).
5.6.4 Smart Recycling Systems In order to make waste and recycling management more sustainable, Makkah is striving to introduce a system where consumers sort their waste into different categories before they throw them in the trash. Rather than just separating the trash into recycling and landfill materials, Makkah is encouraging citizens to separate their trash into food, plastics, papers, and metals to boost the efficiency of recyclable material recovery. The municipality is also introducing solar- powered trash containers that are equipped with trash volume sensors to control the massive amounts of waste produced, as well as an underground system of pipes to move solid waste (Elhassan, Ahmed, & AbdAlhalem, 2019).
5.7 Smart Communication
Advances in Internet capable devices and networks have made vast data sharing networks a reality. This section explores the benefits of smart communication systems and networks.
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5.7.1 Smart Communication Systems M2M Cellular Solutions (Figure 5.4) produced a new cellular modem that can connect freight vehicles to their coordinating station, resulting in reliable communications and data exchange between the two components (UNICOM Global, 2019).
Figure 5.4 M2M Cellular Solutions Diagram (UNICOM Global, 2019)
5.7.2 Smart Communication Networks The number of devices that are capable of connecting to the Internet through Wi-Fi is increasing drastically, and this network of devices is the foundation of the Internet of things (IoT). IoT refers to devices communicating with one another and sharing data. This will allow for greater data exchange and will improve economic, health, and social domains, as illustrated in Figure 5.5 (Al- Fuqaha, Guizani, Mohammadi, Aledhari, & Ayyash, 2015).
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Figure 5.5 Smart Communication Networks overview (Al-Fuqaha et al., 2015)
5.7.3 Crowdsourced Data Collection Crowdsourced data collection is the method of collecting data on a large population through the provision of a service that motivates individuals to share data. Crowdsourcing is usually performed through the internet. It is a valuable data collection strategy often used to recognize trends in consumption and monitor system performance in real-time (Basu, 2018)
5.7.4 Internet of Things (IoT) The Internet of Things is the network of smart devices and objects that have the capacity to connect and share data via the Internet. IoT is connecting all of the domains of everyday life for quick data exchange and easy access to critical information (Hikumwa, 2018). Figure 5.6 depicts some of the broad components of IoT.
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Figure 5.6 Components of IoT (Hikumwa, 2018)
5.7.5 High Speed & Secure Data Network Direct short-range communications (DSRC) is a project of the U.S Department of Transportation and it focuses on a vehicle to vehicle communication for improved safety (Murray, 2016).
5.7.6 Public Wi-Fi In order to decrease the digital divide, a number of cities and establishments provide free public Wi-Fi areas (Tucson Parks & Recreation, 2019).
5.7.7 Smart Safety, Security and Monitoring Smart communication systems facilitate transmission of information about safety or security threats quickly and easily. In addition, individuals under duress can quickly summon for help without having to make a physical phone call.
5.7.8 Information Kiosk Information kiosks are a convenient platform to provide residents and visitors information about services, businesses, tourist attractions, routes, and procedures to complete a certain civic process. These information kiosks can be placed strategically and connected through IoT further enabling ease of access and use.
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5.8 Smart Education Systems
Technology improves educational systems by providing accessible online learning options and new ways to monitor and study learning habits. This section summarizes a few aspects of smart education systems.
5.8.1 Adaptive Learning & Counseling New smart sensors can collect data on student performance so that teachers can recognize trends in a student’s learning ability (Deloitte, 2019) and then customize learning modules to facilitate student success by targeting areas where they need help.
5.8.2 Online Learning Tools Online learning options are being combined with traditional learning practices, and this is yielding great results. This new teaching approach has seen improved test scores and academic performance in more than 80% of students (Deloitte, 2019).
5.8.3 Lifelong Learning The emergence of new jobs and the development of new skills is making lifetime learning a permanent fixture in the professional world (Deloitte, 2019).
5.8.4 Online Education Online education is the future of education. Online learning options are the best fit for most higher-level learning degrees because they offer flexible learning schedules that can be customized and molded to the users' preference (EZTalks, 2017).
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6 Developing a Vision and Action Plan
6.1 Summary
The examples presented in this report are but a few of the many smart transportation and smart city initiatives underway across the country. In reviewing these and other case studies, it is clear that the implementation of smart technologies is a multi-year effort that needs to be undertaken in phases, with the first phase of initial technology deployment and testing. Technologies such as smart parking, smart corridors, bike sharing, connected and autonomous vehicles, smart LED light fixtures, 5G communication technology, DSRC communication technology, and Internet of things (IoT) are the top trending technologies being implemented in the United States and around the world. It is clear that 5G is the next generation of technology that is much faster and has a wider-band than 4.5G LTE; autonomous vehicles and high definition maps both need 5G technology for implementation. DSRC is the short-range communication that is typically used in vehicle to vehicle (V2V) and vehicle to everything (V2X) communication; this technology will remain a useful tool in smart transportation and smart government domains. IoT is an indoor, low cost, long battery life, and high bandwidth mechanism to transfer data over a network without the need for human-to-human or human- to-computer interaction.
As has been seen in a number of case studies, including the City of Tempe, one of the first steps needed to implement smart regions successfully is public meetings and hearings where residents can learn about the benefits of smart technologies and can convey their own priorities. The benefits of transitioning to smart transportation technologies can be seen in transportation safety, energy consumption and air quality, increased efficiency of transportation systems, improved accessibility and mobility for the general population, disabled and disadvantaged or underserved communities.
6.2 SWOT Analysis
Federal, state, local and regional stakeholders all play a role in the development and implementation of Smart Region technologies. However each of the stakeholders has its own unique strengths and weaknesses. That determines in which areas it will be the most efficient and effective to focus the efforts. SWOT analysis is a commonly used framework to examine and determine the Strengths, Weaknesses, Opportunities, and Threats.
When applied to MAG, results of the SWOT analysis can be organized as shown in Figure 6.1.
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Advancing Detrimental to Core Values Core Values
Strengths: Weaknesses:
• Established forum of • Complex jurisdictional governments and other key structure and system of
stakeholders for the political interests Infrastructure development • Complex coordination and funding between stakeholders on
Internal • Established regional data technical levels, inefficiencies hub on the regional level • Designated regional resulting from disparate
transportation planning and technical systems and funding authority in approaches accordance with federal and • Limited funding for
state laws technology
Opportunities: Threats:
• Support of the technological • High level of uncertainty in innovations at the state and technological, economic,
local levels political, funding and
• Strong tech industry and regulatory environment universities relevant to technology
External • Robust regional partnerships • Rapidly changing technology
• Potential inefficiencies and duplications in multiple overlapping initiatives
Figure 6.1 SWOT analysis
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6.3 Next Steps
The inventory and taxonomy of smart region technologies presented in this document serves as a basis for identifying candidate technologies that may be deployed in the region. However this report does not attempt to provide a comprehensive analysis or inventory of Smart Region developments. It is neither a regional technology plan nor a detailed list of future projects and actions. The report provides is a starting point to have more involved and in-depth discussions on regional level and a snapshot of some of the projects that we thought are interesting and can lead to positive future developments in the technology field. It also demonstrates that the discussions and planning cannot be conducted in the mobility space alone, smart technologies and partnerships may occur in a number of intertwined application areas including data, safety, parking, lighting, logistics, first-mile last-mile connectivity, ride-hailing, and autonomous vehicle deployment.
MAG recently issued an on-call solicitation for smart technology deployment. Many vendors expressed interest and proposed a variety of technologies for potential deployment in the region. In order to exchange information and learn more about the various technology solutions that are being developed and offered by various vendors, a workshop should be held. The workshop will bring together technology vendors, cities and jurisdictions, MAG staff, and university task force members. The workshop will provide an opportunity for vendors to present their technology solutions and for MAG and its members to discuss the prospects of testing one or more technology solutions in the real world. It is envisioned that one or more technologies may be selected for demonstration applications by October 2019.
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