Planning for automated vehicles in Edmonton Final report Deliverable for: Autonomous Vehicles Study Update City of Edmonton Submitted by: Antonio Loro Consulting Inc. 443 W. 23rd Ave. Vancouver, BC V5Y 2H5 [email protected] Submitted to: Department of Sustainable Development City Planning Branch 13th Floor, Century Place 9803 - 102A Avenue Edmonton, Alberta T5J 3A3 10 October 2016 Planning for automated vehicles in Edmonton – Final report EXECUTIVE SUMMARY This report summarizes key results from work that was conducted for the City of Edmonton Department of Sustainable Development. The views expressed in this report are those of the consultant and do not necessarily represent those of the City of Edmonton. Some vehicle automation technologies, such as adaptive cruise control, are already available on the market, while significantly more advanced technologies are being developed. Vehicles that can drive themselves in any situation with no human intervention may be decades away, but they could emerge sooner, and less advanced but still powerful technologies will emerge in the very near term. All of these technologies could produce significant impacts on travel and land use in Edmonton. Automation in private light-duty vehicles and taxis could make travel faster and easier, increase road capacity on some roads, and reduce parking demand. However, automated cars have the potential to also produce negative impacts, such as increased vehicle travel due to induced demand, increased congestion on city streets, and a tendency toward more spatially dispersed development. In addition, some benefits, such as increased freeway capacity, may manifest slowly, since they are dependent on high levels of adoption of highly advanced technologies. In contrast, if automation is applied to public transit buses, the frequency and capacity of transit could be significantly improved. This could lead to increased mode share, thus mitigating the tendency toward increased vehicle travel and supporting more spatially compact, resource-efficient development. Importantly, many of these benefits could begin to materialize in the near term. Levels of vehicle automation In the taxonomy of vehicle automation developed by the Society of Automotive Engineers (SAE), Level 1 describes systems where either steering or speed control may be automated, but not both simultaneously. In Level 2, the system controls both steering and speed simultaneously, but the human driver must continuously monitor the vehicle’s performance and must be available to take control with no notice. In Level 3, the driver need not monitor but must be available to take control within a short time when requested by the system. Level 4 refers to a vehicle that can drive itself without any need for human intervention, but that can only do so in specific situations. This includes automated vehicles that may not be highly sophisticated but that nevertheless can operate without human intervention while in controlled environments. Such environments could include specified roads such as freeways, lanes that are dedicated exclusively for the use of automated vehicles, or private zones such as campuses. In Level 5, the system can drive itself in any situation without any need for a i Antonio Loro Consulting Inc. – 10 October 2016 Planning for automated vehicles in Edmonton – Final report human to monitor or be available to take over. Level 5 would make possible applications such as self-driving private vehicles and driverless taxis. Automation technologies: state of the art Vehicle automation technologies use information provided by a variety of sensors, including radar, LIDAR (a remote sensing technology that detects objects via reflected laser light), cameras, infrared cameras, ultrasound, GPS (Global Positioning System), accelerometers, and others. Automated vehicles can also use information provided via wireless communications with other equipped vehicles or entities in the environment – this is referred to as V2V (vehicle to vehicle), V2I (vehicle to infrastructure), or more generally as V2X (vehicle to vehicle, infrastructure, or other entities). Level 1 technologies are currently available in a number of vehicles on the market. Lane- keeping technologies use cameras, radar, and other sensors to detect the position of a vehicle relative to lane markings and/or the vehicle ahead to maintain its position in the lane. Adaptive cruise control maintains the vehicle’s speed at a desired level while adjusting speed as necessary to safely follow the vehicle ahead according to distance and speed data provided by radar. Cooperative adaptive cruise control is a related technology that uses V2V to detect the movements of other vehicles; this technology has been tested but is not available on the market. Level 2 technologies, which simultaneously control steering and speed, are beginning to emerge onto the market. For example, Mercedes and Tesla have introduced such technologies into some of their vehicles. Several projects to develop higher levels of automation are underway. Google is developing automated light-duty vehicles, and is also developing a Level 4, lightweight, two-passenger low-speed automated vehicle that would travel at a maximum of 40 km/h. Google’s vehicles rely especially on a rooftop LIDAR (a sensor that scans the environment with laser light) that develops a detailed 3D map of the environment, which is compared against a map that was developed beforehand while manually driving the route. While Google’s fleet has been test- driven over long distances, the vehicles are continuously monitored by test drivers who take over control when situations arise that may be beyond the capability of the automated system. Other projects, such as the CityMobil2 project in Europe, also aim to automate low-speed operation of lightweight vehicles. This approach greatly reduces the technical challenges involved in achieving full automation. These vehicles have been tested in cities in Italy, France, Greece, Finland, and other countries. Such vehicles could operate in restricted areas, such as university and business campuses, retirement communities, hospital sites, and pedestrian areas, and could provide “first and last mile” access to and from public transit routes. ii Antonio Loro Consulting Inc. – 10 October 2016 Planning for automated vehicles in Edmonton – Final report Automation applied to transit buses can enable operation in narrow rights-of-way, precise docking at bus stations, bus platooning, and fully automated driving. Many of these applications were demonstrated as far back as 2003 by PATH (Partners for Advanced Transportation Technology) in California, and various forms of bus automation have been implemented in locations in Europe, Japan, and the US. Challenges in developing higher levels of automation In order to attain higher levels of automation, such as Level 5, several issues must be resolved. There are major technical challenges. Sensors currently do not function reliably in certain weather conditions, such as rain and snow. Automated systems have difficulties in interpreting sensed data in complex, unstructured, highly dynamic environments, which are common in cities. Map-based systems, such as that used by Google, can become confused when their reference maps have not been updated to reflect changes in the environment. It is also difficult for automated systems to predict the behaviour of vehicles, pedestrians, and other objects. Another problem is to determine how automated vehicles should drive in situations where human drivers rely on eye contact or otherwise communicate with other road users. A related problem is that in order to ensure public acceptance of the technologies, the vehicles will likely need to be capable of driving more safely than humans; to ensure this level of safety, extensive testing will be necessary. In addition, the technologies are currently expensive – for example, it has been reported that the LIDAR used in Google’s test vehicles costs $75,000. It is anticipated that costs of sensors and other components will drop substantially, though it is uncertain when and to what degree this will happen. Programming an automated vehicle also raises ethical challenges, as some driving situations may require choosing between alternatives that impose different levels of risk on different road users. Legal issues must be addressed. While several jurisdictions, including the province of Ontario, have legalized the testing of automated vehicles with human monitors on public roads, before the public can use Level 3, 4, or 5 vehicles, where the vehicle need not be continuously monitored by a human, it will be necessary to clarify the legality of the operation of such vehicles. Liability must also be clarified: if an automated system is driving, blame for a crash may be distributed among various parties, such as an auto manufacturer, a designer of system iii Antonio Loro Consulting Inc. – 10 October 2016 Planning for automated vehicles in Edmonton – Final report components, or a computer programmer. The need to resolve human factors issues – such as ensuring that human drivers perform monitoring or backup tasks as required – could slow the emergence of Level 2 and 3 systems in particular. Security and privacy are also concerns, especially for systems equipped with V2X. Hackers could cause vehicles to crash or otherwise cause problems. Privacy advocates are also concerned about protecting the data on the movements of vehicle users. Timelines of emergence of higher