Motivated by the requirements of highly effective customized bus (CB) service and by the rapid growth of autonomous electric vehicles (AEVs), this paper studies a new optimization model for the autonomous electric customized bus (AECB) service, aiming at minimizing operating costs and improving vehicles’ efficient use. The proposed model contains two phases: (i) optimization of the vehicle routing, charging operation and passenger-to-vehicle assignment for the fixed travel demands, and (ii) re-optimization of the service according to real-time dynamic travel requests. A solution approach is developed to address the proposed model based on adaptive large neighborhood search (ALNS). The extensive empirical analysis, conducted by considering real-world data on a largescale instance, demonstrates the efficiency of the proposed approach and the quality of the generated solutions.
|Title of host publication
|25th IEEE International Conference on Intelligent Transportation Systems
|Subtitle of host publication
|Number of pages
|Published - 1 Nov 2022