Skip to main content
Intended for healthcare professionals
Restricted access
Research article
First published online July 28, 2020

First-Mile-Last-Mile Collector-Distributor System using Shared Autonomous Mobility

Abstract

High costs of owning fully-automated or autonomous vehicles (AVs) will fuel the demand for shared mobility, with zero driver costs. Although sharing sounds good for the transport system, congestion can easily rise without adequate policy measures. Many or all public transit lines will continue to exist, and carefully-designed policies can be implemented to make good use of fixed public assets, like commuter- and light-rail lines. In this study, a shared AV (SAV) fleet is analyzed as a potential solution to the first-mile-last-mile (FMLM) problem for access to and from public transit. Essentially, SAVs are analyzed as collector-distributor systems for these mass-movers and compared with a door-to-door (D2D) service. Results from an agent-based simulation of Austin, Texas, show that SAVs have the potential to help solve FMLM transit problems when fare benefits are provided to transit users. Restricting SAV use for FMLM trips increases transit coverage, lowers average access and egress walking distance, and shifts demand away from park-and-ride and long walk trips. When SAVs are available for both D2D use and FMLM trips, high SAV fares help maintain transit demand, without which the transit demand may decrease significantly, affecting the transit supply and the overall system reliability. Policy makers and planners should be wary of this shift away from transit and may be able to increase transit usage using policies tested in this study.

Get full access to this article

View all access and purchase options for this article.

References

1. Shaheen S. A., Coehn A., Zohdy I. Shared Mobility: Current Practices and Guiding Principles. Publication FHWA-HOP-16-022. Federal Highway Administration, Washington, D.C., 2016.
2. Krueger R., Rashidi T. H., Rose J. M. Preferences for Shared Autonomous Vehicles. Transportation Research Part C: Emerging Technologies, Vol. 69, 2016, pp. 343–355. https://doi.org/10.1016/j.trc.2016.06.015.
3. Kockelman K., Boyles S., Claudel C., Stone P., Loftus-Otway L., Sturgeon P., Sharon G., Gurumurthy K. M., Huang Y., Simoni M., Lei T., Patel R., He D., Mohamed A., Liu J., Yarmohammadi S., Thorn E., Wagner W., Stewart D., Albert M., Hanna J. Phase 2 – Bringing Smart Transport to Texans: Ensuring the Benefits of a Connected and Autonomous Transport System in Texas. Publication FHWA/TX-18/0-6838-3. Texas Department of Transportation, Austin, 2018.
4. Fagnant D. J., Kockelman K. M., Bansal P. Operations of Shared Autonomous Vehicle Fleet for Austin, Texas, Market. Transportation Research Record: Journal of the Transportation Research Board, 2015. 2536: 98–106.
5. Levin M. W., Kockelman K. M., Boyles S. D., Li T. A General Framework for Modeling Shared Autonomous Vehicles with Dynamic Network-Loading and Dynamic Ride-Sharing Application. Computers, Environment and Urban Systems, Vol. 64, 2017, pp. 373–383. https://doi.org/10.1016/j.compenvurbsys.2017.04.006.
6. Simoni M. D., Kockelman K. M., Gurumurthy K. M., Bischoff J. Congestion Pricing in a World of Self-Driving Vehicles: An Analysis of Different Strategies in Alternative Future Scenarios. Transportation Research Part C: Emerging Technologies, Vol. 98, 2019, pp. 167–185. https://doi.org/10.1016/j.trc.2018.11.002.
7. Agatz N., Erera A. L., Savelsbergh M. W. P., Wang X. Dynamic Ride-Sharing: A Simulation Study in Metro Atlanta. Procedia – Social and Behavioral Sciences, Vol. 17, 2011, pp. 532–550. https://doi.org/10.1016/j.sbspro.2011.04.530.
8. Fagnant D. J., Kockelman K. M. Dynamic Ride-Sharing and Fleet Sizing for a System of Shared Autonomous Vehicles in Austin, Texas. Transportation, Vol. 45, No. 1, 2018, pp. 143–158. https://doi.org/10.1007/s11116-016-9729-z.
9. Gurumurthy K. M., Kockelman K. M. Analyzing the Dynamic Ride-Sharing Potential for Shared Autonomous Vehicle Fleets using Cellphone Data from Orlando, Florida. Computers, Environment and Urban Systems, Vol. 71, 2018, pp. 177–185. https://doi.org/10.1016/j.compenvurbsys.2018.05.008.
10. Gurumurthy K. M., Kockelman K. M., Simoni M. D. Benefits and Costs of Ride-Sharing in Shared Automated Vehicles across Austin, Texas: Opportunities for Congestion Pricing. Transportation Research Record: Journal of the Transportation Research Board, 2019. 2673: 548–556.
11. Kittelson & Associates, Inc., Parsons Brinckerhoff; KFH Group, Inc., and Texas A&M Transportation Institute. TCRP Report 165: Transit Capacity and Quality of Service Manual, Third Edition. Transportation Research Board of the National Academies, Washington, D.C., 2013.
12. El-Geneidy A., Grimsrud M., Wasfi R., Tétreault P., Surprenant-Legault J. New Evidence on Walking Distances to Transit Stops: Identifying Redundancies and Gaps using Variable Service Areas. Transportation, Vol. 41, No. 1, 2014, pp. 193–210. https://doi.org/10.1007/s11116-013-9508-z.
13. Wang H., Odoni A. Approximating the Performance of a “Last Mile” Transportation System. Transportation Science, Vol. 50, No. 2, 2016, pp. 659–675. https://doi.org/10.1287/trsc.2014.0553.
14. Liu Z., Jia X., Cheng W. Solving the Last Mile Problem: Ensure the Success of Public Bicycle System in Beijing. Procedia – Social and Behavioral Sciences, Vol. 43, 2012, pp. 73–78. https://doi.org/10.1016/j.sbspro.2012.04.079.
15. Kim S., Ulfarsson G. F., Todd Hennessy J. Analysis of Light Rail Rider Travel Behavior: Impacts of Individual, Built Environment, and Crime Characteristics on Transit Access. Transportation Research Part A: Policy and Practice, Vol. 41, No. 6, 2007, pp. 511–522. https://doi.org/10.1016/j.tra.2006.11.001.
16. Martin E., Shaheen S. The Impact of Carsharing on Public Transit and Non-Motorized Travel: An Exploration of North American Carsharing Survey Data. Energies, Vol. 4, No. 11, 2011, pp. 2094–2114. https://doi.org/10.3390/en4112094.
17. Westervelt M., Huang E., Schank J., Borgman N., Fuhrer T., Peppard C., Narula-Woods R. UpRouted: Exploring Microtransit in The United States. ENO Center for Transportation, 2018.
18. Reck D. J., Axhausen K. W. Subsidized Ridesourcing for the First/Last Mile: How Valuable for Whom?Presented at 99th Annual Meeting of the Transportation Research Board, Washington, D.C., 2020.
19. Shaheen S., Chan N. Mobility and the Sharing Economy: Potential to Facilitate the First- and Last-Mile Public Transit Connections. https://www.ingentaconnect.com/content/alex/benv/2016/00000042/00000004/art00005. Accessed July 24, 2019.
20. Liang X., de A. Correia G. H., van Arem B. Optimizing the Service Area and Trip Selection of an Electric Automated Taxi System Used for the Last Mile of Train Trips. Transportation Research Part E: Logistics and Transportation Review, Vol. 93, 2016, pp. 115–129. https://doi.org/10.1016/j.tre.2016.05.006.
21. Scheltes A., de Almeida Correia G. H. Exploring the Use of Automated Vehicles as Last Mile Connection of Train Trips through an Agent-Based Simulation Model: An Application to Delft, Netherlands. International Journal of Transportation Science and Technology, Vol. 6, No. 1, 2017, pp. 28–41. https://doi.org/10.1016/j.ijtst.2017.05.004.
22. Shen Y., Zhang H., Zhao J. Integrating Shared Autonomous Vehicle in Public Transportation System: A Supply-Side Simulation of the First-Mile Service in Singapore. Transportation Research Part A: Policy and Practice, Vol. 113, 2018, pp. 125–136. https://doi.org/10.1016/j.tra.2018.04.004.
23. Farhan J., Chen T. D., Zhang Z. Leveraging Shared Autonomous Electric Vehicles for First/Last Mile Mobility. Presented at 97th Annual Meeting of the Transportation Research Board, Washington, D.C., 2018.
24. Moorthy A., De Kleine R., Good G., Keoleian J., Lewis G. Shared Autonomous Vehicles as a Sustainable Solution to the Last Mile Problem: A Case Study of Ann Arbor-Detroit Area. SAE International Journal of Passenger Cars – Electronic and Electrical Systems, Vol. 10, No. 2, 2017. https://doi.org/10.4271/2017-01-1276.
25. Stiglic M., Agatz N., Savelsbergh M., Gradisar M. Enhancing Urban Mobility: Integrating Ride-Sharing and Public Transit. Computers & Operations Research, Vol. 90, 2018, pp. 12–21. https://doi.org/10.1016/j.cor.2017.08.016.
26. Alemi F., Rodier C. Simulation of Ridesourcing using Agent-Based Demand and Supply Models Regional: Potential Market Demand for First Mile Transit Travel and Reduction in Vehicle Miles Traveled in the San Francisco Bay Area. Presented at 97th Annual Meeting of the Transportation Research Board, Washington, D.C., 2018.
27. Rodier C., Jaller M., Pourrahmani E., Bischoff J., Freedman J., Pahwa A. Automated Vehicle Scenarios: Simulation of System-Level Travel Effects using Agent-Based Demand and Supply Models in the San Francisco Bay Area. California Department of Transportation, 2018.
28. Pinto H. K. R., de F., Hyland M. F., Verbas İ. Ö., Mahmassani H. S. Integrated Mode Choice and Dynamic Traveler Assignment-Simulation Framework to Assess the Impact of a Suburban First-Mile Shared Autonomous Vehicle Fleet Service on Transit Demand. Presented at 97th Annual Meeting of the Transportation Research Board, Washington, D.C., 2018.
29. Pinto H. K. R. F., Hyland M. F., Mahmassani H. S., Verbas I. Ö. Joint Design of Multimodal Transit Networks and Shared Autonomous Mobility Fleets. Transportation Research Part C: Emerging Technologies, Vol. 113, 2020, pp. 2–20. https://doi.org/10.1016/j.trc.2019.06.010.
30. Huang Y., Kockelman K., Garikapati V., Zhu L., Young S. Use of Shared Automated Vehicles for First-Mile Last-Mile Service: Micro-Simulation of Rail-Transit Connections in Austin, Texas. Presented at 99th Annual Meeting of the Transportation Research Board, Washington, D.C., 2020.
31. Sieber L., Ruch C., Hörl S., Axhausen K. W., Frazzoli E. Improved Public Transportation in Rural Areas with Self-Driving Cars: A Study on the Operation of Swiss Train Lines. Transportation Research Part A: Policy and Practice, Vol. 134, 2020, pp. 35–51. https://doi.org/10.1016/j.tra.2020.01.020.
32. Leich G., Bischoff J. Should Autonomous Shared Taxis Replace Buses? A Simulation Study. Transportation Research Procedia, Vol. 41, 2019, pp. 450–460. https://doi.org/10.1016/j.trpro.2019.09.076.
33. Horni A., Nagel K., Axhausen K. W. The Multi-Agent Transport Simulation MATSim. Ubiquity Press, London, 2016.
34. Liu J., Kockelman K. M., Bösch P. M., Ciari F. Tracking a System of Shared Autonomous Vehicles across the Austin, Texas Network using Agent-Based Simulation. Transportation, Vol. 44, No. 6, 2017, pp. 1261–1278. https://doi.org/10.1007/s11116-017-9811-1.
35. Poletti F., Bösch P. M., Ciari F., Axhausen K. W. Public Transit Route Mapping for Large-Scale Multimodal Networks. ISPRS International Journal of Geo-Information, Vol. 6, No. 9, 2017, p. 268. https://doi.org/10.3390/ijgi6090268.
36. Capital Metropolitan Transportation Authority. Metro Performance Dashboard: Ridership. https://capmetro.org/ridership-stats/. Accessed July 21, 2019.
37. Perone J. S. Advantages and Disadvantages of Fare-Free Transit Policy. Publication NCTR-473-133. National Center for Transportation Research, 2002.

Cite article

Cite article

Cite article

OR

Download to reference manager

If you have citation software installed, you can download article citation data to the citation manager of your choice

Share options

Share

Share this article

Share with email
EMAIL ARTICLE LINK
Share on social media

Share access to this article

Sharing links are not relevant where the article is open access and not available if you do not have a subscription.

For more information view the Sage Journals article sharing page.

Information, rights and permissions

Information

Published In

Article first published online: July 28, 2020
Issue published: October 2020

Rights and permissions

© National Academy of Sciences: Transportation Research Board 2020.
Request permissions for this article.

Authors

Affiliations

Krishna Murthy Gurumurthy
Department of Civil, Architectural and Environmental Engineering, The University of Texas at Austin, Austin, TX
Kara M. Kockelman
Department of Civil, Architectural and Environmental Engineering, The University of Texas at Austin, Austin, TX
Natalia Zuniga-Garcia
Department of Civil, Architectural and Environmental Engineering, The University of Texas at Austin, Austin, TX

Notes

Kara M. Kockelman, [email protected]

Author Contributions

The authors confirm contribution to the paper as follows: study conception and design: K. M. Gurumurthy, N. Zuniga-Garcia, K. Kockelman; methodology: K. M. Gurumurthy; analysis and interpretation of results: K. M. Gurumurthy, N. Zuniga-Garcia, K. Kockelman; draft manuscript preparation: K. M. Gurumurthy, N. Zuniga-Garcia, K. Kockelman. All authors reviewed the results and approved the final version of the manuscript.

Metrics and citations

Metrics

Journals metrics

This article was published in Transportation Research Record: Journal of the Transportation Research Board.

VIEW ALL JOURNAL METRICS

Article usage*

Total views and downloads: 939

*Article usage tracking started in December 2016


Altmetric

See the impact this article is making through the number of times it’s been read, and the Altmetric Score.
Learn more about the Altmetric Scores



Articles citing this one

Receive email alerts when this article is cited

Web of Science: 0

Crossref: 20

  1. O’Hare Airport Short-Term Ground Transportation Modal Demand Forecast ...
    Go to citation Crossref Google Scholar
  2. A column-generation matheuristic approach for optimizing first-mile ri...
    Go to citation Crossref Google Scholar
  3. Automating the first and last mile? Reframing the ‘challenges’ of ever...
    Go to citation Crossref Google Scholar
  4. Increasing Shared Mobility Use in Low Population Suburbs and Urban Fri...
    Go to citation Crossref Google Scholar
  5. Integrated Public Transportation System with Shared Autonomous Vehicle...
    Go to citation Crossref Google Scholar
  6. Fostering synergy between transit and Autonomous Mobility-on-Demand sy...
    Go to citation Crossref Google Scholar
  7. Exploring motivating factors and constraints of using and adoption of ...
    Go to citation Crossref Google Scholar
  8. Understanding the Relationships Among E-scooter Ridership, Transit Des...
    Go to citation Crossref Google Scholar
  9. An agent-based model for assessing the financial viability of autonomo...
    Go to citation Crossref Google Scholar
  10. Equilibrium analysis of trip demand for autonomous taxi services in Na...
    Go to citation Crossref Google Scholar
  11. A general maximum-stability dispatch policy for shared autonomous vehi...
    Go to citation Crossref Google Scholar
  12. Analysis of integrated uses of dockless bike sharing and ridesourcing ...
    Go to citation Crossref Google Scholar
  13. Dynamic ride-sharing impacts of greater trip demand and aggregation at...
    Go to citation Crossref Google Scholar
  14. Integrating shared mobility services with public transit in areas of l...
    Go to citation Crossref Google Scholar
  15. Population Synthesis by Disaggregating OD Matrices with Time-Progressi...
    Go to citation Crossref Google Scholar
  16. Factors influencing public awareness of autonomous vehicles: Empirical...
    Go to citation Crossref Google Scholar
  17. Shared autonomous vehicles implementation for the first and last-mile ...
    Go to citation Crossref Google Scholar
  18. Simulation of price, customer behaviour and system impact for a cost-c...
    Go to citation Crossref Google Scholar

Figures and tables

Figures & Media

Tables

View Options

Get access

Access options

If you have access to journal content via a personal subscription, university, library, employer or society, select from the options below:


Alternatively, view purchase options below:

Purchase 24 hour online access to view and download content.

Access journal content via a DeepDyve subscription or find out more about this option.

View options

PDF/ePub

View PDF/ePub

Full Text

View Full Text