IDEAS home Printed from https://ideas.repec.org/a/eee/transa/v160y2022icp114-125.html
   My bibliography  Save this article

Dynamic ride-sharing impacts of greater trip demand and aggregation at stops in shared autonomous vehicle systems

Author

Listed:
  • Gurumurthy, Krishna Murthy
  • Kockelman, Kara M.

Abstract

Sharing vehicles and rides may become the norm with public use of fully-automated self-driving vehicles in the near future, assuming pandemic-related health concerns fade. Dynamic ride-sharing (DRS) or ride-pooling of trips can significantly improve system performance by lowering empty vehicle-miles traveled (eVMT) and increasing average vehicle occupancy (AVO). With several cities looking to promote efficient curb space use, especially with the use of pickup and drop-off locations (PUDOs), this study explores the impacts of PUDOs on DRS rates and AVO values. Various PUDO spacings and trip-demand densities were studied, across the Bloomington, Illinois region, using the agent-based simulator POLARIS. Results reveal that greater PUDO spacing or distances between stops and higher levels of SAV use or trip demand increase AVO (by up to 20% per 4-seater SAV, on average) and decrease SAV VMT (by up to 27%) compared to door-to-door SAV fleet operations without DRS or PUDOs. A quarter-mile PUDO spacing is recommended in downtown regions, similar to current transit stop spacing, to keep walking trips short and demand relatively high. At 0.25 mi PUDO spacings (thoughtfully placed, using origin and destination clusters), travelers walked less than 5 min at either trip end, on average, while 0.5 mi spacings led to another 1 min (approximately) of walking. More evenly distributed and higher SAV demand can save up to 39% total VMT from use of DRS and PUDO stops. It is also important to prepare for queuing areas at PUDOs in settings of high trip density, to limit curbside congestion.

Suggested Citation

  • Gurumurthy, Krishna Murthy & Kockelman, Kara M., 2022. "Dynamic ride-sharing impacts of greater trip demand and aggregation at stops in shared autonomous vehicle systems," Transportation Research Part A: Policy and Practice, Elsevier, vol. 160(C), pages 114-125.
    • Handle: RePEc:eee:transa:v:160:y:2022:i:c:p:114-125
    DOI: 10.1016/j.tra.2022.03.032
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0965856422000878
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tra.2022.03.032?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. Auld, Joshua & Mohammadian, Abolfazl(Kouros), 2012. "Activity planning processes in the Agent-based Dynamic Activity Planning and Travel Scheduling (ADAPTS) model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(8), pages 1386-1403.
    2. Fagnant, Daniel J. & Kockelman, Kara, 2015. "Preparing a nation for autonomous vehicles: opportunities, barriers and policy recommendations," Transportation Research Part A: Policy and Practice, Elsevier, vol. 77(C), pages 167-181.
    3. Mustapha Harb & Yu Xiao & Giovanni Circella & Patricia L. Mokhtarian & Joan L. Walker, 2018. "Projecting travelers into a world of self-driving vehicles: estimating travel behavior implications via a naturalistic experiment," Transportation, Springer, vol. 45(6), pages 1671-1685, November.
    4. Gurumurthy, Krishna Murthy & Kockelman, Kara M., 2020. "Modeling Americans’ autonomous vehicle preferences: A focus on dynamic ride-sharing, privacy & long-distance mode choices," Technological Forecasting and Social Change, Elsevier, vol. 150(C).
    5. Quarles, Neil & Kockelman, Kara M. & Lee, Jooyong, 2021. "America’s fleet evolution in an automated future," Research in Transportation Economics, Elsevier, vol. 90(C).
    6. Tu, Meiting & Li, Ye & Li, Wenxiang & Tu, Minchao & Orfila, Olivier & Gruyer, Dominique, 2019. "Improving ridesplitting services using optimization procedures on a shareability network: A case study of Chengdu," Technological Forecasting and Social Change, Elsevier, vol. 149(C).
    7. 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.
    8. Daniel J. Fagnant & Kara M. Kockelman, 2018. "Dynamic ride-sharing and fleet sizing for a system of shared autonomous vehicles in Austin, Texas," Transportation, Springer, vol. 45(1), pages 143-158, January.
    9. 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.
    10. Lavieri, Patrícia S. & Bhat, Chandra R., 2019. "Modeling individuals’ willingness to share trips with strangers in an autonomous vehicle future," Transportation Research Part A: Policy and Practice, Elsevier, vol. 124(C), pages 242-261.
    11. 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.
    12. Agatz, Niels A.H. & Erera, Alan L. & Savelsbergh, Martin W.P. & Wang, Xing, 2011. "Dynamic ride-sharing: A simulation study in metro Atlanta," Transportation Research Part B: Methodological, Elsevier, vol. 45(9), pages 1450-1464.
    13. 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.
    14. Hall, Jonathan D. & Palsson, Craig & Price, Joseph, 2018. "Is Uber a substitute or complement for public transit?," Journal of Urban Economics, Elsevier, vol. 108(C), pages 36-50.
    15. 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).
    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. Omar Rifki, 2024. "Autonomous Ride-Sharing Service Using Graph Embedding and Dial-a-Ride Problem: Application to the Last-Mile Transit in Lyon City," Mathematics, MDPI, vol. 12(4), pages 1-17, February.

    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. Gurumurthy, Krishna Murthy & Kockelman, Kara M., 2021. "Impacts of shared automated vehicles on airport access and operations, with opportunities for revenue recovery: Case Study of Austin, Texas," Research in Transportation Economics, Elsevier, vol. 90(C).
    2. 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.
    3. 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.
    4. Nadafianshahamabadi, Razieh & Tayarani, Mohammad & Rowangould, Gregory, 2021. "A closer look at urban development under the emergence of autonomous vehicles: Traffic, land use and air quality impacts," Journal of Transport Geography, Elsevier, vol. 94(C).
    5. Mohamad Shatanawi & Mohammed Hajouj & Belal Edries & Ferenc Mészáros, 2022. "The Interrelationship between Road Pricing Acceptability and Self-Driving Vehicle Adoption: Insights from Four Countries," Sustainability, MDPI, vol. 14(19), pages 1-32, October.
    6. Gurumurthy, Krishna Murthy & Kockelman, Kara M., 2020. "Modeling Americans’ autonomous vehicle preferences: A focus on dynamic ride-sharing, privacy & long-distance mode choices," Technological Forecasting and Social Change, Elsevier, vol. 150(C).
    7. Wang, Jinghui & Yang, Hao, 2023. "Low carbon future of vehicle sharing, automation, and electrification: A review of modeling mobility behavior and demand," Renewable and Sustainable Energy Reviews, Elsevier, vol. 177(C).
    8. Levin, Michael W., 2022. "A general maximum-stability dispatch policy for shared autonomous vehicle dispatch with an analytical characterization of the maximum throughput," Transportation Research Part B: Methodological, Elsevier, vol. 163(C), pages 258-280.
    9. Cokyasar, Taner & Larson, Jeffrey, 2020. "Optimal assignment for the single-household shared autonomous vehicle problem," Transportation Research Part B: Methodological, Elsevier, vol. 141(C), pages 98-115.
    10. Zwick, Felix & Kuehnel, Nico & Hörl, Sebastian, 2022. "Shifts in perspective: Operational aspects in (non-)autonomous ride-pooling simulations," Transportation Research Part A: Policy and Practice, Elsevier, vol. 165(C), pages 300-320.
    11. Vij, Akshay & Ryan, Stacey & Sampson, Spring & Harris, Susan, 2020. "Consumer preferences for on-demand transport in Australia," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 823-839.
    12. Noruzoliaee, Mohamadhossein & Zou, Bo, 2022. "One-to-many matching and section-based formulation of autonomous ridesharing equilibrium," Transportation Research Part B: Methodological, Elsevier, vol. 155(C), pages 72-100.
    13. 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.
    14. Wu, Min & Wang, Nanxi & Yuen, Kum Fai, 2023. "Can autonomy level and anthropomorphic characteristics affect public acceptance and trust towards shared autonomous vehicles?," Technological Forecasting and Social Change, Elsevier, vol. 189(C).
    15. Wadud, Zia & Mattioli, Giulio, 2021. "Fully automated vehicles: A cost-based analysis of the share of ownership and mobility services, and its socio-economic determinants," Transportation Research Part A: Policy and Practice, Elsevier, vol. 151(C), pages 228-244.
    16. Mourad, Abood & Puchinger, Jakob & Chu, Chengbin, 2019. "A survey of models and algorithms for optimizing shared mobility," Transportation Research Part B: Methodological, Elsevier, vol. 123(C), pages 323-346.
    17. 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).
    18. Dean, Matthew D. & Kockelman, Kara M., 2021. "Spatial variation in shared ride-hail trip demand and factors contributing to sharing: Lessons from Chicago," Journal of Transport Geography, Elsevier, vol. 91(C).
    19. Al-Kanj, Lina & Nascimento, Juliana & Powell, Warren B., 2020. "Approximate dynamic programming for planning a ride-hailing system using autonomous fleets of electric vehicles," European Journal of Operational Research, Elsevier, vol. 284(3), pages 1088-1106.
    20. Krueger, Rico & Rashidi, Taha H. & Vij, Akshay, 2020. "A Dirichlet process mixture model of discrete choice: Comparisons and a case study on preferences for shared automated vehicles," Journal of choice modelling, Elsevier, vol. 36(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:eee:transa:v:160:y:2022:i:c:p:114-125. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/547/description#description .

    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.