All-Links-Based E-Hailing Pricing and Surcharge Mechanism for Transportation System Performance Improvement

Abstract

E-hailing services, in which riders request rides from their mobile devices, have rapidly developed into a viable transportation alternative for many travelers. This technology has changed the set of choices for travelers and has shifted travel patterns, most significantly away from traditional taxi services. However, several issues have arisen during this expansion. In this paper, an economical approach is proposed which considers both the effects of the travelers’ route choices and travel demand patterns. In this approach, we assume that all links can be surcharged for those using e-hailing services, and a heuristic process is applied to address this computationally difficult problem. A cost inverse function is introduced to update the demand changes along paths with different rates of e-hailing surcharges. The method is demonstrated on the mid-size network of Sioux Falls, South Dakota, and on the large-scale city network of Anaheim, California. Results indicate that an optimal price could efficiently reduce e-hailing service demand during congestion hours and improve the transportation system performance to system optimal level.