Price and Time Optimization for Utility-Aware Taxi Dispatching.

The recent enhancement of taxi dispatch services with information technology has enabled data-driven pricing and dispatch. However, existing studies failed to address differences in individual priorities as regards money savings and time savings, leading to non-optimal taxi pricing and dispatch. In this paper, we formulate a new optimization problem that yields optimized price and time proposals for each requester according to their priorities. To consider the requester’s priorities, we introduce an individual requester’s acceptance probability model for price and required time, which is widely used in transportation economics. The proposals of price and time combinations yielded by our method enhance both the requester’s satisfaction and the service provider’s profit. Since the optimization problem is difficult to solve because its objective values are hard to evaluate and discontinuous, we construct a fast approximation algorithm by utilizing the characteristics of the problem. Simulations using real-world datasets show that the proposed framework increases both the requester’s satisfaction and service provider’s profit.