IDEAS home Printed from https://ideas.repec.org/a/kap/transp/v44y2017i6d10.1007_s11116-017-9811-1.html
   My bibliography  Save this article

Tracking a system of shared autonomous vehicles across the Austin, Texas network using agent-based simulation

Author

Listed:
  • Jun Liu

    (The University of Texas at Austin)

  • Kara M. Kockelman

    (The University of Texas at Austin)

  • Patrick M. Boesch

    (IVT, ETH Zurich)

  • Francesco Ciari

    (IVT, ETH Zurich)

Abstract

This study provides a large-scale micro-simulation of transportation patterns in a metropolitan area when relying on a system of shared autonomous vehicles (SAVs). The six-county region of Austin, Texas is used for its land development patterns, demographics, networks, and trip tables. The agent-based MATSim toolkit allows modelers to track individual travelers and individual vehicles, with great temporal and spatial detail. MATSim’s algorithms help improve individual travel plans (by changing tour and trip start times, destinations, modes, and routes). Here, the SAV mode requests were simulated through a stochastic process for four possible fare levels: $0.50, $0.75, $1, and $1.25 per trip-mile. These fares resulted in mode splits of 50.9, 12.9, 10.5, and 9.2% of the region’s person-trips, respectively. Mode choice results show longer-distance travelers preferring SAVs to private, human-driven vehicles (HVs)—thanks to the reduced burden of SAV travel (since one does not have to drive the vehicle). For travelers whose households do not own an HV, SAVs (rather than transit, walking and biking) appear preferable for trips under 10 miles, which is the majority of those travelers’ trip-making. It may be difficult for traditional transit services and operators to survive once SAVs become available in regions like Austin, where dedicated rail lines and bus lanes are few. Simulation of SAV fleet operations suggest that higher fare rates allow for greater vehicle replacement (ranging from 5.6 to 7.7 HVs per SAV, assuming that the average SAV serves 17–20 person-trips per day); when fares rise, travel demands shift away from longer trip distances. Empty vehicle miles traveled by the fleet of SAVs ranged from 7.8 to 14.2%, across the scenarios in this study. Implications of mobility and sustainability benefits of SAVs are also discussed in the paper.

Suggested Citation

  • Jun Liu & Kara M. Kockelman & Patrick M. Boesch & Francesco Ciari, 2017. "Tracking a system of shared autonomous vehicles across the Austin, Texas network using agent-based simulation," Transportation, Springer, vol. 44(6), pages 1261-1278, November.
    • Handle: RePEc:kap:transp:v:44:y:2017:i:6:d:10.1007_s11116-017-9811-1
    DOI: 10.1007/s11116-017-9811-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11116-017-9811-1
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s11116-017-9811-1?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Novosel, T. & Perković, L. & Ban, M. & Keko, H. & Pukšec, T. & Krajačić, G. & Duić, N., 2015. "Agent based modelling and energy planning – Utilization of MATSim for transport energy demand modelling," Energy, Elsevier, vol. 92(P3), pages 466-475.
    2. Chen, T. Donna & Kockelman, Kara M. & Hanna, Josiah P., 2016. "Operations of a shared, autonomous, electric vehicle fleet: Implications of vehicle & charging infrastructure decisions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 243-254.
    3. Chester, Mikhail & Horvath, Arpad, 2009. "Life-cycle Energy and Emissions Inventories for Motorcycles, Diesel Automobiles, School Buses, Electric Buses, Chicago Rail, and New York City Rail," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt6z37f2jr, Institute of Transportation Studies, UC Berkeley.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Talebian, Ahmadreza & Mishra, Sabyasachee, 2022. "Unfolding the state of the adoption of connected autonomous trucks by the commercial fleet owner industry," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 158(C).
    2. Iacobucci, Riccardo & McLellan, Benjamin & Tezuka, Tetsuo, 2018. "Modeling shared autonomous electric vehicles: Potential for transport and power grid integration," Energy, Elsevier, vol. 158(C), pages 148-163.
    3. Huang, Yantao & Kockelman, Kara M. & Quarles, Neil, 2020. "How will self-driving vehicles affect U.S. megaregion traffic? The case of the Texas Triangle," Research in Transportation Economics, Elsevier, vol. 84(C).
    4. Ding, Zhong-Jun & Dai, Zong & Chen, Xiqun (Michael) & Jiang, Rui, 2020. "Simulating on-demand ride services in a Manhattan-like urban network considering traffic dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    5. Kim, Sung Hoo & Circella, Giovanni & Mokhtarian, Patricia L., 2019. "Identifying latent mode-use propensity segments in an all-AV era," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 192-207.
    6. Nodjomian, Adam T. & Kockelman, Kara, 2019. "How does the built environment affect interest in the ownership and use of self-driving vehicles?," Journal of Transport Geography, Elsevier, vol. 78(C), pages 115-134.
    7. Mo, Dong & Chen, Xiqun (Michael) & Zhang, Junlin, 2022. "Modeling and Managing Mixed On-Demand Ride Services of Human-Driven Vehicles and Autonomous Vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 157(C), pages 80-119.
    8. Loeb, Benjamin & Kockelman, Kara M., 2019. "Fleet performance and cost evaluation of a shared autonomous electric vehicle (SAEV) fleet: A case study for Austin, Texas," Transportation Research Part A: Policy and Practice, Elsevier, vol. 121(C), pages 374-385.
    9. Richter, Maximilian A. & Hagenmaier, Markus & Bandte, Oliver & Parida, Vinit & Wincent, Joakim, 2022. "Smart cities, urban mobility and autonomous vehicles: How different cities needs different sustainable investment strategies," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    10. Becker, Henrik & Becker, Felix & Abe, Ryosuke & Bekhor, Shlomo & Belgiawan, Prawira F. & Compostella, Junia & Frazzoli, Emilio & Fulton, Lewis M. & Guggisberg Bicudo, Davi & Murthy Gurumurthy, Krishna, 2020. "Impact of vehicle automation and electric propulsion on production costs for mobility services worldwide," Transportation Research Part A: Policy and Practice, Elsevier, vol. 138(C), pages 105-126.
    11. Kassens-Noor, Eva & Dake, Dana & Decaminada, Travis & Kotval-K, Zeenat & Qu, Teresa & Wilson, Mark & Pentland, Brian, 2020. "Sociomobility of the 21st century: Autonomous vehicles, planning, and the future city," Transport Policy, Elsevier, vol. 99(C), pages 329-335.
    12. Almlöf, Erik & Nybacka, Mikael & Pernestål, Anna & Jenelius, Erik, 2022. "Will leisure trips be more affected than work trips by autonomous technology? Modelling self-driving public transport and cars in Stockholm, Sweden," Transportation Research Part A: Policy and Practice, Elsevier, vol. 165(C), pages 1-19.
    13. Shi, Yuji & Blainey, Simon & Sun, Chao & Jing, Peng, 2020. "A literature review on accessibility using bibliometric analysis techniques," Journal of Transport Geography, Elsevier, vol. 87(C).
    14. Wali, Behram & Santi, Paolo & Ratti, Carlo, 2023. "Are californians willing to use shared automated vehicles (SAV) & renounce existing vehicles? An empirical analysis of factors determining SAV use & household vehicle ownership," Technological Forecasting and Social Change, Elsevier, vol. 195(C).
    15. Marletto, Gerardo, 2019. "Who will drive the transition to self-driving? A socio-technical analysis of the future impact of automated vehicles," Technological Forecasting and Social Change, Elsevier, vol. 139(C), pages 221-234.
    16. Kaddoura, Ihab & Bischoff, Joschka & Nagel, Kai, 2020. "Towards welfare optimal operation of innovative mobility concepts: External cost pricing in a world of shared autonomous vehicles," Transportation Research Part A: Policy and Practice, Elsevier, vol. 136(C), pages 48-63.
    17. Mehdizadeh, Milad & Nordfjaern, Trond & Klöckner, Christian A., 2022. "A systematic review of the agent-based modelling/simulation paradigm in mobility transition," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    18. Kaltenhäuser, Bernd & Werdich, Karl & Dandl, Florian & Bogenberger, Klaus, 2020. "Market development of autonomous driving in Germany," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 882-910.
    19. Nahmias-Biran, Bat-hen & Oke, Jimi B. & Kumar, Nishant, 2021. "Who benefits from AVs? Equity implications of automated vehicles policies in full-scale prototype cities," Transportation Research Part A: Policy and Practice, Elsevier, vol. 154(C), pages 92-107.
    20. Li, Li & Pantelidis, Theodoros & Chow, Joseph Y.J. & Jabari, Saif Eddin, 2021. "A real-time dispatching strategy for shared automated electric vehicles with performance guarantees," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Metais, M.O. & Jouini, O. & Perez, Y. & Berrada, J. & Suomalainen, E., 2022. "Too much or not enough? Planning electric vehicle charging infrastructure: A review of modeling options," Renewable and Sustainable Energy Reviews, Elsevier, vol. 153(C).
    2. Østergaard, P.A. & Lund, H. & Thellufsen, J.Z. & Sorknæs, P. & Mathiesen, B.V., 2022. "Review and validation of EnergyPLAN," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    3. Xu, Xiaodan & Liu, Haobing & Passmore, Reid & Patrick, Tyler & Gbologah, Franklin & Rodgers, Michael O. & Guensler, Randall, 2018. "Fuel and Emissions Calculator (FEC), Version 3.0, Summary Report," Institute of Transportation Studies, Working Paper Series qt59z12905, Institute of Transportation Studies, UC Davis.
    4. Yavas, Volkan & Yavaş Tez, Özge, 2023. "Consumer intention over upcoming utopia: Urban air mobility," Journal of Air Transport Management, Elsevier, vol. 107(C).
    5. Lucio Ciabattoni & Stefano Cardarelli & Marialaura Di Somma & Giorgio Graditi & Gabriele Comodi, 2021. "A Novel Open-Source Simulator Of Electric Vehicles in a Demand-Side Management Scenario," Energies, MDPI, vol. 14(6), pages 1-16, March.
    6. Pernestål Brenden , Anna & Kristoffersson , Ida, 2018. "Effects of driverless vehicles: A review of simulations," Working papers in Transport Economics 2018:11, CTS - Centre for Transport Studies Stockholm (KTH and VTI).
    7. Graabak, Ingeborg & Wu, Qiuwei & Warland, Leif & Liu, Zhaoxi, 2016. "Optimal planning of the Nordic transmission system with 100% electric vehicle penetration of passenger cars by 2050," Energy, Elsevier, vol. 107(C), pages 648-660.
    8. Wang, Hua & Zhao, De & Meng, Qiang & Ong, Ghim Ping & Lee, Der-Horng, 2020. "Network-level energy consumption estimation for electric vehicles considering vehicle and user heterogeneity," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 30-46.
    9. Yantao Huang & Kara M. Kockelman, 2020. "What will autonomous trucking do to U.S. trade flows? Application of the random-utility-based multi-regional input–output model," Transportation, Springer, vol. 47(5), pages 2529-2556, October.
    10. Li, Dun & Huang, Youlin & Qian, Lixian, 2022. "Potential adoption of robotaxi service: The roles of perceived benefits to multiple stakeholders and environmental awareness," Transport Policy, Elsevier, vol. 126(C), pages 120-135.
    11. Herc, Luka & Pfeifer, Antun & Duić, Neven & Wang, Fei, 2022. "Economic viability of flexibility options for smart energy systems with high penetration of renewable energy," Energy, Elsevier, vol. 252(C).
    12. Riccardo Iacobucci & Benjamin McLellan & Tetsuo Tezuka, 2018. "The Synergies of Shared Autonomous Electric Vehicles with Renewable Energy in a Virtual Power Plant and Microgrid," Energies, MDPI, vol. 11(8), pages 1-20, August.
    13. Martin Adler & Stefanie Peer & Tanja Sinozic, 2019. "Autonomous, Connected, Electric Shared vehicles (ACES) and public finance: an explorative analysis," Tinbergen Institute Discussion Papers 19-005/VIII, Tinbergen Institute.
    14. Meyer, Jonas & Becker, Henrik & Bösch, Patrick M. & Axhausen, Kay W., 2017. "Autonomous vehicles: The next jump in accessibilities?," Research in Transportation Economics, Elsevier, vol. 62(C), pages 80-91.
    15. Liu, Zhiyong & Li, Ruimin & Dai, Jingchen, 2022. "Effects and feasibility of shared mobility with shared autonomous vehicles: An investigation based on data-driven modeling approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 156(C), pages 206-226.
    16. Hyland, Michael & Mahmassani, Hani S., 2020. "Operational benefits and challenges of shared-ride automated mobility-on-demand services," Transportation Research Part A: Policy and Practice, Elsevier, vol. 134(C), pages 251-270.
    17. Borge-Diez, David & Icaza, Daniel & Açıkkalp, Emin & Amaris, Hortensia, 2021. "Combined vehicle to building (V2B) and vehicle to home (V2H) strategy to increase electric vehicle market share," Energy, Elsevier, vol. 237(C).
    18. Zhou, Fan & Zheng, Zuduo & Whitehead, Jake & Washington, Simon & Perrons, Robert K. & Page, Lionel, 2020. "Preference heterogeneity in mode choice for car-sharing and shared automated vehicles," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 633-650.
    19. Moneim Massar & Imran Reza & Syed Masiur Rahman & Sheikh Muhammad Habib Abdullah & Arshad Jamal & Fahad Saleh Al-Ismail, 2021. "Impacts of Autonomous Vehicles on Greenhouse Gas Emissions—Positive or Negative?," IJERPH, MDPI, vol. 18(11), pages 1-23, May.
    20. Chang, Miguel & Lund, Henrik & Thellufsen, Jakob Zinck & Østergaard, Poul Alberg, 2023. "Perspectives on purpose-driven coupling of energy system models," Energy, Elsevier, vol. 265(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:kap:transp:v:44:y:2017:i:6:d:10.1007_s11116-017-9811-1. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.