Ridesharing on Timetabled Transport Services: A Multiagent Planning Approach

Abstract: Ridesharing, that is, the problem of finding parts of routes that can be shared by several travelers with different points of departure and destinations, is a complex, multiagent decision-making problem. The problem has been widely studied but only for the case of ridesharing using freely moving vehicles not bound to fixed routes and/or schedules—ridesharing on timetabled public transport services has not been previously considered. In this article, we address this problem and propose a solution employing strategic multiagent planning that guarantees that for any shared journey plan found, each individual is better off taking the shared ride rather than traveling alone, thus providing a clear incentive to participate in it. We evaluate the proposed solution on real-world scenarios in terms of the algorithm’s scalability and the ability to address the inherent trade-off between cost savings and the prolongation of journey duration. The results show that under a wide range of circumstances our algorithm finds attractive shared journey plans. In addition to serving as a basis for traveler-oriented ridesharing service, our system allows stakeholders to determine appropriate pricing policies to incentivize group travel and to predict the effects of potential service changes.

Citation: J. Hrncir, M. Rovatsos, and M. Jakob. Ridesharing on Timetabled Transport Services: A Multiagent Planning Approach, Journal of Intelligent Transportation Systems, 19(1):89-105, 2015.

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About P. Andreadis

Pre-Doctoral Research Assistant in AI and Social Computation @ University of Edinburgh.

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