Modeling urban taxi services with e-hailings: A queueing network approach

摘要

The rise of e-hailing taxis has significantly altered urban transportation system and led to a competitive taxi market with both traditional street-hailing and e-hailing taxis. The various taxi services provide similar door-to-door rides, thus compete with each other. Meanwhile, the expanding fleet size of e-hailing taxis, together with considerable number of traditional taxicabs, influence the urban road network performance, which can also in turn affect taxi mode choice and operation. In this study, we propose an innovative modeling structure for the competitive taxi market and capture the interactions not only within the taxi market but also between the taxi market and urban road system.The model is built on a network linking a certain number of queues, derived from both the taxi and urban road system. Considering both the passenger and vehicle arrivals, we utilize an assembly-like queue SM/M/1 for passenger-vehicle matching within the taxi system, which controls how many and how frequently vehicles drive from the taxi system to the urban road system. A common multi-server M/M/c queue that can account for road capacity is proposed for the urban road system and a feedback of network states is sent back to the taxi system. Then the stationary state distributions, as well as asymptotic properties, of the queueing network are discussed.An example is designed based on data from New York City. Numerical results show that the proposed modeling structure, together with the corresponding approximation method, can capture dynamics within high demand areas and, in particular, a spatially balanced system. Overall, this study shows how the queueing network approach can measure aggregated performance of various taxi services, for instance, not only the waiting/searching time during passenger-vehicle matching but also the delays in the urban road network. Furthermore, the model can be generalized to study the control and management of taxi markets.