On demand ride sharing: Scheduling of an autonomous bus fleet for last mile travel

Autonomous buses are expected to expand the mobility-on-demand options in cities in the next 10 years. An essential aspect of ensuring optimal usage of fleets of autonomous buses is the task of scheduling. This paper presents a scheduling approach based on the construction of all possible trips used to formulate an optimization problem. While in the past most research is focused on the scheduling of taxi trips, there is an increasing interest in the research for the scheduling of last-mile travel options. A street network has been generated based on open street map data as a basis for the scheduling. All possible combinations of buses and requests are calculated, and for each of those trips, a close to optimal order of requests is created. These are used to formulate the optimization problem, calculating a close to optimal assignment of requests on the buses. The approach has considered constraints such as maximum waiting time, travel delay, and targets to exploit shared trips for higher efficiency. Experiments have been carried out in a simulated environment of a university campus area with fleets of up to 10 vehicles. By performing various trials with changing parameters, the influence of the constraints on waiting time and travel delay to the scheduling is determined. Depending on the setup, service rates above 90%, while trails with strict constraints show that the approach can handle short-term requests. Based on the results, a use case-specific composition of the autonomous bus fleet can be done.