Research Article Intelligent Systems to Enhance Last Mile Connectivity for Upcoming Smart Cities in India Moushila De1, Shailja Sikarwar2, Vijay Kumar3 Abstract Due to exorbitant migration in urban areas in the last few decades, increasing vehicle ownerships, traffic congestion and rising extreme air pollution have resulted more and more cities in India to opt for various mass rapid transit systems such as metro rail, mono rail and BRT systems etc. But cities still faces the problem of last mile connectivity. Most of the cities don’t have proper last mile connectivity facilities. First mile/last mile connections are made in a number of ways, these include: walking, bicycling, private automobile, metro feeder, bus service local bus, E-rickshaw, cycle rickshaw and auto rickshaw. This article is an attempt to understand the existing last mile connectivity issues in various cities of India especially in Delhi and how with the help of various Information and Communication based solutions, last mile connectivity can be enhanced in upcoming smart cities in India. This article basically focuses on seamless integration with other modes physically, technically and institutionally, smart parking management through RFID based technology and biometric devices, electronic road pricing, use of mobile GIS technology in safety and security process, installation of passenger information system and operation control centre and multiuse mobility card, Green CAB “dial a rickshaw facility etc. These above intelligent system and smart solutions can be used to enhance last mile connectivity in upcoming smart cities in India. Keywords: Automatic ticket vending machine, Geographical information system, Electronic road pricing, Intelligent technologies, Radio frequency identification device Introduction Computational and Intelligent technologies provide a strong and efficient support to transportation infrastructure to address the issues of Last Mile Connectivity. People often have problem in starting their trip i.e. from their home. A person has beyond his residence to reach the station located at main transport network. Providing best last mile connectivity options can reduces the cases of various crimes and also helps in the prevention of crime. It will also ensure safety and security of people specially women. During the last few decades, total number of cars has increased traffic congestion and related urban transport problem also arise in cities of India. Traditional method of an aid in this case is a feeder bus that is provided beyond the transport network to meet these needs but the problem is more than just feeder buses. Very few people prefer walking and cycling due to poor conditions of road infrastructure etc. Therefore, it is necessary to focus and enhance last mile connectivity in various cities of India. Last mile connectivity should not be just an option at metro ends but be treated as an opportunities as a user’s home. It is also necessary to suggest various intelligent technologies solutions. 1Student, MURP (Urban and Rural Planning) India. 2Associate Professor, 3Professor, Faculty of Architecture and Urban Planning, D. C. R. University of Science and Technology, Murthal, Haryana, India. Correspondence: Moushila De, MURP (Urban and Rural Planning) India. E-mail Id: [email protected] How to cite this article:De M, Sikarwar S, Kuma V. Intelligent Systems to Enhance Last Mile Connectivity for Upcoming Smart Cities in India. J Adv Res Const Urban Arch 2017; 2(3&4): 16-31. ISSN: 2456-9925 © ADR Journals 2017. All Rights Reserved. J. Adv. Res. Const. Urban Arch. 2017; 2(3&4) De M et al. The Research including the rise in private vehicles have led to chaos and disruption around metro station. It is the reason behind The effort aims to understand the first and last mile congestion on access road to metro station. connectivity and its relationship with a commuter’s choice of transit options for conceiving a journey and its impact To understand the existing last mile connectivity, four on public transport ridership and also evolve intelligent stations (Saket, INA, Vishwavidyalaya, Sultanpur) of Delhi technologies and smart technologies based solutions to metro stations were choosen based on ridership data ensure or to enhance various last mile connectivity options up to January 2017, last mile connectivity modes quality in the upcoming smart cities in India. assessment through Reconnaissance survey, abutting land use around yellow line metro stations, trip generating and Existing status of Last Mile Connectivity in India trip attracting metro stations through reconnaissance survey, activity intensity around the stations, typology of In most of the Indian cities the conditions of last mile the stations. conditions is very pathetic. In most of the cities people are facing the problem of uncomfortable environment, long Figure 1 explains the abutting land use plan of selected case waiting hours, long walking distance, overcrowded, traffic study stations. Based on the land use pattern of the area, congestions etc. A survey was conducted to understand the Saket, Sultanpur, INA and Vishwavidyalaya metro station last mile connectivity scenario in Delhi. From the survey, are categorized into trip producing area or trip attracting it was found that presently only 41 out of 138 stations area, also categorized into high, mid and low ridership. It of Delhi MRTS are served by feeder services. Haphazard also explains the factors affecting the impact of last mile supply of alternate modes around mass transit stations connectivity on metro ridership. Figure 1.(a) Abutting land use plan of Vishwavidyalaya; (b) Saket; (c) Sultanpur; (d) INA metro stations 17 ISSN: 2456-9925 De M et al. J. Adv. Res. Const. Urban Arch. 2017; 2(3&4) Table 1.Metro station area profile Attributes Saket Metro Sultanpur INA Metro Vishwavidyalaya Station Metro Station Station Metro Station Planning zones Zone F Zone J Zone D Zone O Public transport Modes Metro feeder bus, Bus, Share Auto, Bus, Auto Rickshaw, Share modes Auto, DTC Buses, E - Rickshaw Auto, Auto, Bus, Grameenseva, College Bus, E - Metro bicycle Rickshaw sharing scheme. Physical Parking Yes Yes No Yes infrastructure Pick up and Yes No Yes No drop off Safety Eyes on Street Fair Poor Fair Fair Activity Fair Poor Fair Good during college hours Dead Spots No No No No Information Fair Poor Fair Fair Conduciveness High Wall - - - - of Street Shade No No No No Access Yes No Yes Yes Visibility Street light Approx. 20 m Approx. more Approx.15 m Approx. 15 m gaps than 30 m Environment Trees Fair Poor Poor Good Noise Average Poor Average Good Foul Smell No No No No Ambience Poor Poor Fair Fair On ground observation also highlighted the fact that all the Inadequate, but Vishwavidyalaya and INA metro stations case study stations are located along busy arterial roads has relative better last mile connectivity than Sultanpur and ring roads causing disruption to the through fare of and Saket métro stations. vehicles. In terms of physical infrastructure, the stations are Source: Retrieved from DMRC on February 2017 Figure 2.Comparative analysis of ridership data It is depicted from the Fig. 2 that Saket has the highest are only because of availability of abutting land use in ridership and footfalls, followed by Vishwavidyalaya and selected case study stations. For IPT operators and NMT INA has the same and mid ridership whereas Sultanpur operators, analysis was focused on current scenario of has the lowest ridership and footfalls. These differences LMC options available and their ownership. Looks like ISSN: 2456-9925 18 J. Adv. Res. Const. Urban Arch. 2017; 2(3&4) De M et al. average expenditure on parking, permits, operation and operated, total time taken, total distance covered, route maintenance of the vehicle were included to get insights or area covered, total number of bicycle taken by passenger of the functioning of the various LMC options available to in a day, rules and regulations applied for people who the commuter. took cycle for rent etc. Feeder bus and bicycle plays an important role for enhancing last mile connectivity in that For Feeder bus operator and bicycle sharing operator, particular area. analysis was focused on total number of feeder bus Figure 3.IPT and NMT survey analysis For private vehicle users, the analysis included various styles LMC options available. An open ended question targeted at of travel and user characteristic. But the main objective the willingness of user to opt for public transport if proper here was to obtain an estimation of the perception of user LMC options and parking mechanisms are in place near for not using public conveyance and its connection with the major PT systems was also admitted. Figure 4.Survey locations 19 ISSN: 2456-9925 De M et al. J. Adv. Res. Const. Urban Arch. 2017; 2(3&4) Figure 5.Types of vehicles surveyed Figure 6.Trip purpose Figure 7.Frequency of tips Table 2.Total distance (kms.) covered by private mode users ISSN: 2456-9925 20 J. Adv. Res. Const. Urban Arch. 2017; 2(3&4) De M et al. Table 3.Average time to last mile Table 4.Average cost paid by private vehicle user for last mile connectivity Reasons for not using Public transport by Private Vehicle Users Figure 8.Private vehicle users survey analysis 21 ISSN: 2456-9925 De M et al. J. Adv. Res. Const. Urban Arch. 2017; 2(3&4) The study incorporates, for commuter category, the aspects trips. The analysis also included several types of LMC of time, cost, and comfort for the overall journey with main modes available, perceived problems, suggestions and user focus on last mile connectivity options involving, “Origin characteristic during peak and non-peak hours. to public transport” and, “Public transport to Destination” Figure 9.Trip distribution by age Figure 10.Trip distribution by gender Figure 11.Trip distribution by education Figure 12.Trip distribution by occupation ISSN: 2456-9925 22 J.