Managing Autonomous Mobility on Demand Systems for Better Passenger Experience

  • Wen ShenEmail author
  • Cristina Lopes
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9387)


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 \(7.65\%\).


Autonomous vehicles Mobility on demand AMOD Systems Agent-based simulation 


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Department of InformaticsUniversity of CaliforniaIrvineUSA

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