Skip to main content

Managing Autonomous Mobility on Demand Systems for Better Passenger Experience

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9387))

Abstract

Autonomous mobility on demand systems, though still in their infancy, have very promising prospects in providing urban population with sustainable and safe personal mobility in the near future. While much research has been conducted on both autonomous vehicles and mobility on demand systems, to the best of our knowledge, this is the first work that shows how to manage autonomous mobility on demand systems for better passenger experience. We introduce the Expand and Target algorithm which can be easily integrated with three different scheduling strategies for dispatching autonomous vehicles. We implement an agent-based simulation platform and empirically evaluate the proposed approaches with the New York City taxi data. Experimental results demonstrate that the algorithm significantly improve passengers’ experience by reducing the average passenger waiting time by up to \(29.82\%\) and increasing the trip success rate by up to \(7.65\%\).

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Agussurja, L., Lau, H.C.: Toward large-scale agent guidance in an urban taxi service (2012). arXiv preprint arXiv:1210.4849

  2. Alshamsi, A., Abdallah, S., Rahwan, I.: Multiagent self-organization for a taxi dispatch system. In: 8th International Conference on Autonomous Agents and Multiagent Systems, pp. 21–28 (2009)

    Google Scholar 

  3. Anderson, J.M., Nidhi, K., Stanley, K.D., Sorensen, P., Samaras, C., Oluwatola, O.A.: Autonomous vehicle technology: A guide for policymakers. Rand Corporation (2014)

    Google Scholar 

  4. Beirão, G., Cabral, J.S.: Understanding attitudes towards public transport and private car: A qualitative study. Transport policy 14(6), 478–489 (2007)

    Article  Google Scholar 

  5. Broggi, A., Buzzoni, M., Debattisti, S., Grisleri, P., Laghi, M.C., Medici, P., Versari, P.: Extensive tests of autonomous driving technologies. IEEE Transactions on Intelligent Transportation Systems 14(3), 1403–1415 (2013)

    Article  Google Scholar 

  6. Čertickỳ, M., Jakob, M., Píbil, R.: Analyzing on-demand mobility services by agent-based simulation. Journal of Ubiquitous Systems & Pervasive Networks 6(1), 17–26 (2015)

    Google Scholar 

  7. Čertickỳ, M., Jakob, M., Píbil, R., Moler, Z.: Agent-based simulation testbed for on-demand transport services. In: Proceedings of the 2014 International Conference on Autonomous Agents and Multi-agent Systems, pp. 1671–1672 (2014)

    Google Scholar 

  8. Chong, Z., Qin, B., Bandyopadhyay, T., Wongpiromsarn, T., Rebsamen, B., Dai, P., Rankin, E., Ang Jr, M.H.: Autonomy for mobility on demand. In: Intelligent Autonomous Systems 12, pp. 671–682. Springer (2013)

    Google Scholar 

  9. Delling, D., Sanders, P., Schultes, D., Wagner, D.: Engineering route planning algorithms. In: Lerner, J., Wagner, D., Zweig, K.A. (eds.) Algorithmics of Large and Complex Networks. LNCS, vol. 5515, pp. 117–139. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  10. Donovan, B., Work, D.: New york city taxi data 2010–2013 (2014). http://publish.illinois.edu/dbwork/open-data/

  11. Downs, A.: Still Stuck in Traffic: Coping with Peak-hour Traffic Congestion. Brookings Institution Press (2005)

    Google Scholar 

  12. Gan, J., An, B., Miao, C.: Optimizing efficiency of taxi systems: scaling-up and handling arbitrary constraints. In: Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems, pp. 523–531 (2015)

    Google Scholar 

  13. Glaschenko, A., Ivaschenko, A., Rzevski, G., Skobelev, P.: Multi-agent real time scheduling system for taxi companies. In: 8th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2009), pp. 29–36. Budapest, Hungary (2009)

    Google Scholar 

  14. Haklay, M., Weber, P.: Openstreetmap: User-generated street maps. IEEE Pervasive Computing 7(4), 12–18 (2008)

    Article  Google Scholar 

  15. Huang, A.S., Moore, D., Antone, M., Olson, E., Teller, S.: Finding multiple lanes in urban road networks with vision and lidar. Autonomous Robots 26(2–3), 103–122 (2009)

    Article  Google Scholar 

  16. Jakob, M., Moler, Z., Komenda, A., Yin, Z., Jiang, A.X., Johnson, M.P., Pěchouček, M., Tambe, M.: Agentpolis: towards a platform for fully agent-based modeling of multi-modal transportation. In: Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems, vol. 3, pp. 1501–1502 (2012)

    Google Scholar 

  17. Lavrinc, D.: BMW builds a self-driving car - that drifts. Wired Magazine (2014)

    Google Scholar 

  18. Lozano-Perez, T., Cox, I.J., Wilfong, G.T.: Autonomous robot vehicles. Springer Science & Business Media (2012)

    Google Scholar 

  19. Maciejewski, M., Nagel, K.: Simulation and dynamic optimization of taxi services in MATSim. VSP Working Paper (2013)

    Google Scholar 

  20. MAPZEN: Mapzen metro extracts: New york City (2015). https://mapzen.com/data/metro-extracts

  21. Markoff, J.: Google cars drive themselves, in traffic. New York Times (2010)

    Google Scholar 

  22. Mitchell, W.J.: Intelligent cities. UOC Papers 5, 1541–1885 (2007)

    Google Scholar 

  23. Mitchell, W.J.: Reinventing the automobile: Personal urban mobility for the 21st century. MIT Press (2010)

    Google Scholar 

  24. Moghadam, P., Wijesoma, W.S., Feng, D.J.: Improving path planning and mapping based on stereo vision and lidar. In: Proceedings of the 10th International Conference on Control, Automation, Robotics and Vision, pp. 384–389. IEEE (2008)

    Google Scholar 

  25. Ontodia: Pediacities neighborhoods of New York city (2015). http://catalog.opendata.city/dataset/pediacities-nyc-neighborhoods

  26. Papadimitratos, P., La Fortelle, A., Evenssen, K., Brignolo, R., Cosenza, S.: Vehicular communication systems: Enabling technologies, applications, and future outlook on intelligent transportation. IEEE Communications Magazine 47(11), 84–95 (2009)

    Article  Google Scholar 

  27. Premebida, C., Ludwig, O., Nunes, U.: Lidar and vision-based pedestrian detection system. Journal of Field Robotics 26(9), 696–711 (2009)

    Article  Google Scholar 

  28. Seow, K.T., Dang, N.H., Lee, D.H.: A collaborative multiagent taxi-dispatch system. IEEE Transactions on Automation Science and Engineering 7(3), 607–616 (2010)

    Article  Google Scholar 

  29. Spieser, K., Treleaven, K., Zhang, R., Frazzoli, E., Morton, D., Pavone, M.: Toward a systematic approach to the design and evaluation of automated mobility-on-demand systems: a case study in singapore. In: Road Vehicle Automation, pp. 229–245. Springer (2014)

    Google Scholar 

  30. Zhang, R., Pavone, M.: Control of robotic mobility-on-demand systems: a queueing-theoretical perspective (2014). arXiv preprint arXiv:1404.4391

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Wen Shen .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Shen, W., Lopes, C. (2015). Managing Autonomous Mobility on Demand Systems for Better Passenger Experience. In: Chen, Q., Torroni, P., Villata, S., Hsu, J., Omicini, A. (eds) PRIMA 2015: Principles and Practice of Multi-Agent Systems. PRIMA 2015. Lecture Notes in Computer Science(), vol 9387. Springer, Cham. https://doi.org/10.1007/978-3-319-25524-8_2

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-25524-8_2

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-25523-1

  • Online ISBN: 978-3-319-25524-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics