Proceedings Abstracts of the Twenty-Fifth International Joint Conference on Artificial Intelligence

An Online Mechanism for Ridesharing in Autonomous Mobility-on-Demand Systems / 475
Wen Shen, Cristina V. Lopes, Jacob W. Crandall

With proper management, Autonomous Mobility-on-Demand (AMoD) Systems have great potential to satisfy the transport demand of urban populations by providing safe, convenient, and affordable ridesharing services. Meanwhile, such systems can substantially decrease private car ownership and use, and thus significantly reduce traffic congestion, energy consumption, and carbon emissions. To achieve this objective, an AMoD system requires private information about the demand from passengers. However, due to self-interestedness, passengers are unlikely to cooperate with the service providers in this regard. Therefore, an online mechanism is desirable if it incentivizes passengers to truthfully report their actual demand. For the purpose of promoting ridesharing, we hereby introduce a posted-price, integrated online ridesharing mechanism (IORS) that satisfies desirable properties such as ex-post incentive compatibility, individual rationality, and budget-balance. Numerical results indicate the competitiveness of IORS compared with two benchmarks, namely the optimal assignment and an offline, auction-based mechanism.