Online Auctions with Dynamic Costs for Ridesharing

• Main Authors: Zhang, Chaoli, Wu, Fan, Gao, Xiaofeng, Chen, Guihai
• Format: Conference Proceeding
• Language: English
• Subjects: Automobiles; Companies; Pricing; Public transportation; Resource management; Surges
• ISSN: 1521-9097; 2690-5965
• DOI: 10.1109/ICPADS.2017.00028

Uber, Lyft and some other companies achieve great business success in the area of ridesharing. However, there are still many issues to be addressed, for instance, the lack of a well-designed rush hour (i.e., when supply is much less than demand) pricing strategy, the seat resources waste and so on. The online ridesharing model fits better to reality but brings significant design challenges. In this paper, we propose a complementary online auction design: No Preemption auction. The auction in ridesharing needs to deal with dynamic costs, which is different from most of the existing auctions and brings significant challenges. We design corresponding online auction mechanism for this model. Our mechanism is truthful with Risk Aversion Hypothesis, budget balanced (i.e., the payment is not less than the cost), computational efficient, individually rational, and make the best use of the seat resources. We give theoretical proof of the truthfulness, budget balance, computational efficiency and individual rationality. We also give a discussion about the general online ridesharing mechanism performance. Finally, we evaluate the performance of our mechanism based on real taxi-trace data in Shanghai. The results show that our mechanism can achieve rather good revenue and social welfare.