Share:


Congestion effects of autonomous taxi fleets

Abstract

Fleets of shared Autonomous Vehicles (AVs) could replace private cars by providing a taxi-like service but at a cost similar to driving a private car. On the one hand, large Autonomous Taxi (AT) fleets may result in increased road capacity and lower demand for parking spaces. On the other hand, an increase in vehicle trips is very likely, as travelling becomes more convenient and affordable, and additionally, ATs need to drive unoccupied between requests. This study evaluates the impact of a city-wide introduction of ATs on traffic congestion. The analysis is based on a multi-agent transport simulation (MATSim) of Berlin (Germany) and the neighbouring Brandenburg area. The central focus is on precise simulation of both real-time AT operation and mixed autonomous/conventional vehicle traffic flow. Different ratios of replacing private car trips with AT trips are used to estimate the possible effects at different stages of introducing such services. The obtained results suggest that large fleets operating in cities may have a positive effect on traffic if road capacity increases according to current predictions. ATs will practically eliminate traffic congestion, even in the city centre, despite the increase in traffic volume. However, given no flow capacity improvement, such services cannot be introduced on a large scale, since the induced additional traffic volume will intensify today’s congestion.


First Published Online: 4 Sept 2017

Keyword : autonomous vehicle, autonomous taxi, taxi dispatching, traffic flow, queue model, large-scale simulation, MATSim

How to Cite
Maciejewski, M., & Bischoff, J. (2018). Congestion effects of autonomous taxi fleets. Transport, 33(4), 971-980. https://doi.org/10.3846/16484142.2017.1347827
Published in Issue
Dec 5, 2018
Abstract Views
32
PDF Downloads
22
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

References

Agatz, N. A. H.; Erera, A. L.; Savelsbergh, M. W. P.; Wang, X. 2011. Dynamic ride-sharing: a simulation study in metro Atlanta, Transportation Research Part B: Methodological 45(9): 1450–1464. https://doi.org/10.1016/j.trb.2011.05.017

Bischoff, J.; Maciejewski, M. 2016a. Autonomous taxicabs in Berlin – a spatiotemporal analysis of service performance, Transportation Research Procedia 19: 176–186. https://doi.org/10.1016/j.trpro.2016.12.078

Bischoff, J.; Maciejewski, M. 2016b. Simulation of city-wide replacement of private cars with autonomous taxis in Berlin, Procedia Computer Science 83: 237–244. https://doi.org/10.1016/j.procs.2016.04.121

Bischoff, J.; Maciejewski, M.; Sohr, A. 2015. Analysis of Berlin’s taxi services by exploring GPS traces, in 2015 International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS), 3–5 June 2015, Budapest, Hungary, 209–215. https://doi.org/10.1109/MTITS.2015.7223258

Burns, L. D.; Scarborough, B. A. 2013. Transforming Personal Mobility. The Earth Institute, Columbia University, New York, NY, US. 43 p. Available from Internet: http://sustainablemobility.ei.columbia.edu/files/2012/12/Transforming-Personal-Mobility-Jan-27-20132.pdf

Ehmke, J. F.; Meisel, S.; Mattfeld, D. C. 2010. Floating car data based analysis of urban travel times for the provision of traffic quality, International Series in Operations Research & Management Science 144: 129–149. https://doi.org/10.1007/978-1-4419-6070-2_9

Erath, A.; Fourie, P.; Van Eggermond, M.; Ordóñez, S.; Chakirov, A.; Axhausen, K. 2012. Large-scale agent-based transport demand model for Singapore. Working Paper. Institute for Transport Planning and Systems, Swiss Federal Institute of Technology Zurich. 40 p. Available from Internet: https://www.ethz.ch/content/dam/ethz/special-interest/baug/ivt/ivt-dam/vpl/reports/701-800/ab790.pdf

Fagnant, D. J; Kockelman, K. M. 2015. Dynamic Ride-Sharing and Optimal Fleet Sizing for a System of Shared Autonomous Vehicles, in Transportation Research Board 94th Annual Meeting, 11–15 January 2015, Washington, DC, US, 1–17.

Fajardo, D.; Au, T.-C.; Waller, S.; Stone, P.; Yang, D. 2011. Automated intersection control: performance of future innovation versus current traffic signal control, Transportation Research Record: Journal of the Transportation Research Board 2259: 223–232. https://doi.org/10.3141/2259-21

Fellendorf, M.; Vortisch, P. 2010. Microscopic traffic flow simulator VISSIM, International Series in Operations Research & Management Science 145: 63–93. https://doi.org/10.1007/978-1-4419-6142-6_2

Friedrich, B. 2015. Verkehrliche Wirkung autonomer Fahrzeuge, in M. Maurer, J. C. Gerdes, B. Lenz, H. Winner (Eds.). Autonomes Fahren, 331–350. https://doi.org/10.1007/978-3-662-45854-9_16 (in German).

Hörl, S. 2016. Implementation of an autonomous taxi service in a multi-modal traffic simulation using MATSim: Master thesis in Complex Adaptive Systems. Chalmers University of Technology, Gothenburg, Sweden. 90 p. Available from Internet: http://publications.lib.chalmers.se/records/fulltext/237733/237733.pdf

Horni, A.; Nagel, K.; Axhausen, K. W. 2016a. Introducing MATSim, in A. Horni, K. Nagel, K. W. Axhausen (Eds.). The Multi-Agent Transport Simulation MATSim, 3–8.

Horni, A.; Nagel, K.; Axhausen, K. W. 2016b. The Multi-Agent Transport Simulation MATSim. Ubiquity Press Ltd. 620 p. https://doi.org/10.5334/baw

Kaddoura, I. 2015. Marginal congestion cost pricing in a multiagent simulation: investigation of the greater Berlin area, Journal of Transport Economics and Policy 49(4): 560–578.

Kickhöfer, B.; Hosse, D.; Turner, K.; Tirachini, A. 2016. Creating an Open MATSim Scenario from Open Data: the Case of Santiago de Chile. VSP Working Paper 16-02. Technical University of Berlin, Germany. 22 p. Available from Internet: http://svn.vsp.tu-berlin.de/repos/public-svn/publications/vspwp/2016/16-02/KickhoeferEtAl2016MatsimSantiago.pdf

Krajzewicz, D.; Erdmann, J.; Behrisch, M., Bieker, L. 2012. Recent development and applications of SUMO – Simulation of Urban MObility, International Journal on Advances in Systems and Measurements 5(3&4): 128–138.

Levin, M. W.; Boyles, S. D. 2016. A multiclass cell transmission model for shared human and autonomous vehicle roads, Transportation Research Part C: Emerging Technologies 62: 103–116. https://doi.org/10.1016/j.trc.2015.10.005

Levin, M. W.; Kockelman, K. M.; Boyles, S. D.; Li, T. 2017. A general framework for modeling shared autonomous vehicles with dynamic network-loading and dynamic ridesharing application, Computers, Environment and Urban Systems 64: 373–383. https://doi.org/10.1016/j.compenvurbsys.2017.04.006

Li, B.; Zhang, D.; Sun, L.; Chen, C.; Li, S.; Qi, G.; Yang, Q. 2011. Hunting or waiting? Discovering passenger-finding strategies from a large-scale real-world taxi dataset, in 2011 IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops), 21–25 March 2011, Seattle, WA, US, 63–68. https://doi.org/10.1109/PERCOMW.2011.5766967

Litman, T. 2015. Autonomous vehicle implementation predictions: implications for transport planning, in Transportation Research Board 94th Annual Meeting, 11–15 January 2015, Washington, DC, US, 1–15.

Kümmel, M.; Busch, F.; Wang, D. Z. W. 2016. Taxi dispatching and stable marriage, Procedia Computer Science 83: 163–170. https://doi.org/10.1016/j.procs.2016.04.112

Maciejewski, M. 2016. Dynamic transport services, in A. Horni, K. Nagel, K. W. Axhausen (Eds.). The Multi-Agent Transport Simulation MATSim, 145–152.

Maciejewski, M. 2010. A comparison of microscopic traffic flow simulation systems for an urban area, Transport Problems – Problemy Transportu 5(4): 27–38.

Maciejewski, M.; Bischoff, J.; Nagel, K. 2016. An assignment-based approach to efficient real-time city-scale taxi dispatching, IEEE Intelligent Systems 31(1): 68–77. https://doi.org/10.1109/MIS.2016.2

Martínez, L. 2015. Urban Mobility System Upgrade: How Shared Self-Driving Cars Could Change City Traffic. Corporate Partnership Board Report. International Transport Forum. 36 p. Available from Internet: https://www.itf-oecd.org/sites/default/files/docs/15cpb_self-drivingcars.pdf

Neumann, A. 2014. A Paratransit-Inspired Evolutionary Process for Public Transit Network Design: PhD Dissertation. Technical University of Berlin, Germany. 267 p.

Rieser, M.; Nagel, K.; Horni, A. 2016. MATSim data containers, in A. Horni, K. Nagel, K. W. Axhausen (Eds.). The Multi-Agent Transport Simulation MATSim, 55–60.

Salanova, J. M.; Estrada, M. A.; Aifadopoulou, G.; Mitsakis, E. 2011. A review of the modeling of taxi services, Procedia – Social and Behavioral Sciences 20: 150–161. https://doi.org/10.1016/j.sbspro.2011.08.020

Salanova Grau, J. M.; Estrada Romeu, M. A. 2015. Agent based modelling for simulating taxi services, Procedia Computer Science 52: 902–907. https://doi.org/10.1016/j.procs.2015.05.162

Salanova Grau, J. M.; Estrada Romeu, M. A., Mitsakis, E.; Stamos, I. 2013. Agent based modeling for simulation of taxi services, Journal of Traffic and Logistics Engineering 1(2): 159–163. https://doi.org/10.12720/jtle.1.2.159-163

Seow, K. T.; Dang, N. H.; Lee, D.-H. 2010. A collaborative multiagent taxi-dispatch system, IEEE Transactions on Automation Science and Engineering 7(3): 607–616. https://doi.org/10.1109/TASE.2009.2028577

Spieser, K.; Treleaven, K.; Zhang, R.; Frazzoli, E.; Morton, D.; Pavone, M. 2014. Toward a systematic approach to the design and evaluation of automated mobility-on-demand systems: a case study in Singapore, in G. Meyer, S. Beiker (Eds.). Road Vehicle Automation, 229–245. https://doi.org/10.1007/978-3-319-05990-7_20

Van Arem, B.; Van Driel, C. J. G.; Visser, R. 2006. The Impact of Cooperative Adaptive Cruise Control on Traffic-Flow Characteristics, IEEE Transactions on Intelligent Transportation Systems 7(4): 429–436. https://doi.org/10.1109/TITS.2006.884615

Veloso, M.; Phithakkitnukoon, S; Bento, C. 2011. Sensing urban mobility with taxi flow, in LBSN’11: Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Location-Based Social Networks, 1–4 November 2011, Chicago, US, 41–44. https://doi.org/10.1145/2063212.2063215

Wadud, Z.; MacKenzie, D.; Leiby, P. 2016. Help or hindrance? The travel, energy and carbon impacts of highly automated vehicles, Transportation Research Part A: Policy and Practice 86: 1–18. https://doi.org/10.1016/j.tra.2015.12.001

Wagner, P. 2015. Steuerung und Management in einem Verkehrssystem mit autonomen Fahrzeugen, in M. Maurer, J. C. Gerdes, B. Lenz, H. Winner (Eds.). Autonomes Fahren, 313–330. https://doi.org/10.1007/978-3-662-45854-9_15 (in German).

Zhan, X.; Hasan, S.; Ukkusuri, S. V.; Kamga, C. 2013. Urban link travel time estimation using large-scale taxi data with partial information, Transportation Research Part C: Emerging Technologies 33: 37–49. https://doi.org/10.1016/j.trc.2013.04.001

Zhan, X.; Qian, X.; Ukkusuri, S. V. 2016. A graph-based approach to measuring the efficiency of an urban taxi service system, IEEE Transactions on Intelligent Transportation Systems 17(9): 2479–2489. https://doi.org/10.1109/TITS.2016.2521862

Zhang, R.; Rossi, F.; Pavone, M. 2016. Routing autonomous vehicles in congested transportation networks: structural properties and coordination algorithms, Robotics: Science and Systems 12: 1–9. https://doi.org/10.15607/RSS.2016.XII.032