A Filtering System for the Large-Scale Dial-A-Ride Problem With Shared Autonomous Vehicles

In this paper, we study a prospective transportation system in which shared autonomous vehicles provide dial-a-ride service for large passenger demands in urban and rural areas. We address this very large-scale problem using a greedy insertion heuristic. Accompanying this heuristic, we propose a filtering system to speed up routing process. The approach includes two specific data structures used as filtering devices, three different filtering modules, and a halt mechanism to control the computation effort spent in exploring the search space for candidate vehicles. The approach also relies on an original route encoding that exploits the topology of the road network. Experimental results show that en-route vehicles can be significantly reduced in such a system, decreasing the vehicle number by more than . And thanks to the filtering system, the execution time can be reduced by almost compared to the classic best-fit insertion heuristic while maintaining a comparable level of solution quality.