Abstract Summary
The era of intelligence transportation is coming. Nonetheless, the transition to an intelligent system will be a gradual process. On the one hand, some zones in the city may be dedicated as autonomous zone with a fully intelligent traffic facility allowing only autonomous vehicles. On the other hand, autonomous and conventional vehicles are both allowed to drive in the remains zone of the network. In this paper, we consider a situation where AVs are deployed by a taxi operating company to serve door-to-door travel requests. Facing this transition period, a flow-based vehicle routing model is developed to determine the optimal fleet size of autonomous and conventional taxis as a function of the gradually increasing coverage of the automated vehicles- only area. Traffic congestion is considered as a dynamically varying travel time with the vehicle flows. In this paper, two service regimes of the company are tested: User Preference Mode (UPM) and System Profit Mode (SPM). The developed model formulations are applied to the case study city of Delft, the Netherlands. The results give insight into the performance of the heterogeneous taxi system on a hybrid network. Strategies are presented on how to adjust the fleet size of autonomous and conventional taxis to get the best system profit while satisfying the mobility demand. The SPM can bring more profit to the operating company by reducing the detour and relocation distance of taxis compared to the UPM.
