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Platooning of Autonomous Public Transport Vehicles: the Influence of Ride Comfort on Travel Delay

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Platooning of Autonomous Public Transport Vehicles: the Influence of Ride Comfort on Travel Delay sustainability Article Platooning of Autonomous Public Transport Vehicles: The Influence of Ride Comfort on Travel Delay Teron Nguyen 1,2,3,* , Meng Xie 2 , Xiaodong Liu 2 , Nimal Arunachalam 2, Andreas Rau 2, Bernhard Lechner 1 , Fritz Busch 4 and Y. D. Wong 3 1 Institute of Road, Railway and Airfield Construction, Technical University of Munich, Baumbachstr. 7, 81245 Munich, Germany; [email protected] 2 Rapid Road Transport, TUMCREATE Ltd., 1 Create Way, #10-02 CREATE Tower, Singapore 138602, Singapore; [email protected] (M.X.); [email protected] (X.L.); [email protected] (N.A.); [email protected] (A.R.) 3 Centre for Infrastructure Systems, Nanyang Technological University, N1-01b-51, 50 Nanyang Avenue, Singapore 639798, Singapore; [email protected] 4 Chair of Traffic Engineering and Control, Technical University of Munich, Arcisstr. 21, 80333 Munich, Germany; [email protected] * Correspondence: [email protected] or [email protected]; Tel.: +65-8376-1636 Received: 3 September 2019; Accepted: 21 September 2019; Published: 24 September 2019 Abstract: The development of advanced technologies has led to the emergence of autonomous vehicles. Herein, autonomous public transport (APT) systems equipped with prioritization measures are being designed to operate at ever faster speeds compared to conventional buses. Innovative APT systems are configured to accommodate prevailing passenger demand for peak as well as non-peak periods, by electronic coupling and decoupling of platooned units along travel corridors, such as the dynamic autonomous road transit (DART) system being researched in Singapore. However, there is always the trade-off between high vehicle speed versus passenger ride comfort, especially lateral ride comfort. This study analyses a new APT system within the urban context and evaluates its performance using microscopic traffic simulation. The platooning protocol of autonomous vehicles was first developed for simulating the coupling/decoupling process. Platooning performance was then simulated on VISSIM platform for various scenarios to compare the performance of DART platooning under several ride comfort levels: three bus comfort and two railway criteria. The study revealed that it is feasible to operate the DART system following the bus standing comfort criterion 2 (ay = 1.5 m/s ) without any significant impact on system travel time. For the DART system operating to maintain a ride comfort of the high-speed train (HST) and light rail transit (LRT), the delay can constitute up to 10% and 5% of travel time, respectively. This investigation is crucial for the ≈ ≈ system delay management towards precisely designed service frequency and improved passenger ride comfort. Keywords: autonomous public transport; passenger ride comfort; travel time; horizontal alignment; microscopic traffic simulation 1. Introduction The emergence of autonomous vehicles (AVs) has engendered innovative solutions for traffic congestion mitigation as well as the improvement of the passenger riding experience. The traveling public can expect level 5 full automation in more than 50% of vehicles by 2030 [1]. Herein, AVs can be readily operated as platoons on the streets with minimum gaps between individual AVs, thereby resulting in a significant increase of road capacity and improving fuel economy [2]. On the other Sustainability 2019, 11, 5237; doi:10.3390/su11195237 www.mdpi.com/journal/sustainability Sustainability 2019, 11, 5237 2 of 14 Sustainability 2019, 11, x FOR PEER REVIEW 2 of 14 hand, by eliminating the driving tasks, vehicle occupants (drivers and passengers) can utilize on-board hand,traveling by timeeliminating for activities the driving such as tasks, reading, vehicle chatting occupants or even working(drivers [and3,4], whichpassengers) is expected can utilize to increase on- boardthe productivity traveling time and for enable activities other such activities as reading, to be executed chatting withinor even a working day [5]. For[3,4], example, which is commuter expected toservices increase in the motion productivity are designed and enable for NEXT’s other activi modularties to self-driving be executed vehicleswithin a withday [5]. built For prototypes example, commuterof autonomous services pods in inmotion Dubai are [6]. designed To achieve for e ffiNEXTcient’smobility modular services, self-driving AV platooningvehicles with in whichbuilt prototypesconsecutive of vehicles autonomous conjugate pods as in a Dubai road-train [6]. To on theachieve street efficient is a good mobility solution. services, AV platooning in whichAs forconsecutive the on-road vehicles autonomous conjugate public as a transport road-train (APT) on the system, street whichis a good is a solution. public transport mode thatAs can for guide the on-road itself without autonomous human public conduction, transport there (APT) is a system, trend of which connecting is a public singular transport modules mode to thatform can platoons guide itself on the without road. human This is conduction, the latest advance there is after a trend the of well-developed connecting singular and implemented modules to formcar platooning platoons on [7 ]the and road. truck This platooning is the latest [8] ad wherevance a after number the well-developed of vehicles are travelingand implemented together andcar platooningelectronically [7] connected.and truck platooning For example, [8] recentwhere researcha number at TUMCREATEof vehicles are in traveling Singapore together is aimed and at electronicallydeveloping a connected. dynamic autonomous For example, road recent transit research (DART) at TUMCREATE system at a much in Singapore higher journey is aimed speed at developingof autonomous a dynamic bus (AB) autonomous platoons (atroad an transit average (DART) speed system of 28km at/h) a thanmuch conventional higher journey buses speed (at of an autonomousaverage speed bus of (AB) 19km platoons/h) to off er(at a an higher average capacity speed level of 28km/h) [9]. With than a vehicle conventional module ofbuses 6m length,(at an average3.1 m height, speed 2.7of m19km/h) width, to and offer capacity a higher of 30capacity passengers level /[9].module, With thea vehicle DART module system isof designed6m length, to 3.1mflexibly height, adapt 2.7m to passenger width, and demand capacity by electronically-linked of 30 passengers/module, platoons the of theDART vehicles system/modules is designed on shared to flexiblyroute segments adapt to and passenger to decouple demand for route by electronically-linked divergence. Relevant platoons studies have of the been vehicles/modules conducted focusing on sharedon scheduled route segments platoon planningand to decouple [10], fleet for sizeroute estimation divergence. [11 ],Relevant and the studies deployment have been framework conducted [12]. focusingSimilar high-speed on scheduled platooning platoon public planning transport [10], can fleet be foundsize estimation in Dubai under [11], testingand the [6 ,13deployment,14] as well frameworkas autonomous [12]. railSimilar rapid high-speed transit in Chinaplatooning (see Figure public1 ).transport can be found in Dubai under testing [6,13,14] as well as autonomous rail rapid transit in China (see Error! Reference source not found.). Figure 1. Examples of autonomous public transport (APT) platooning in (a) Singapore, source: Figure 1. Examples of autonomous public transport (APT) platooning in (a) Singapore, source: https://www.tum-create.edu.sg/;(b) NEXT’s modular self-driving vehicles designed in Dubai, source: https://www.tum-create.edu.sg/; (b) NEXT’s modular self-driving vehicles designed in Dubai, source: http://www.next-future-mobility.com/; and (c) Autonomous rail rapid transit in China, source: http: http://www.next-future-mobility.com/; and (c) Autonomous rail rapid transit in China, source: //www.crrcgc.cc/zzs. http://www.crrcgc.cc/zzs. Although automation may bring down the driver-cost in dense networks such as the urban Although automation may bring down the driver-cost in dense networks such as the urban context, the requirements of the schedule, fleet size, and route optimization are also raised [15]. context, the requirements of the schedule, fleet size, and route optimization are also raised [15]. The The application of APT platooning in a large-scale operation has required a new concept in order application of APT platooning in a large-scale operation has required a new concept in order to to maintain a fixed timetabling frequency, e.g., every 5 minutes, for passenger transport. This is maintain a fixed timetabling frequency, e.g. every 5 minutes, for passenger transport. This is different different from car platooning for private use or truck platooning for freight transport. Any deviation from car platooning for private use or truck platooning for freight transport. Any deviation is is expected to affect the system performance regarding travel time and speed, which reduces the expected to affect the system performance regarding travel time and speed, which reduces the whole whole APT system’s reliability. Thus far, recent studies have focused on technological developments APT system’s reliability. Thus far, recent studies have focused on technological developments and and often ignore the human factors which are of utmost importance in attracting car users to use often ignore the human factors which are of utmost importance in attracting car users to use public public transport. The vehicle speeds are affected by
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