Joint Optimal Scheduling for a Mixed Bus Fleet Under Micro Driving Conditions

The emergence of electric buses (EBs) is expected to alleviate traffic pollution. However, the promotion of EBs requires a long transition period; during this period, EBs cannot wholly replace conventional buses (CBs). In addition, compared with CBs, EBs have long charging times and short cruising ranges, resulting in short operating times being available for the scheduling process. Therefore, to effectively schedule EBs and CBs, we propose a joint optimal scheduling model for a mixed bus fleet under micro driving conditions. First, we estimate the bus trip time under micro driving conditions. To ensure that all bus transportation tasks can be executed as planned, we propose a buffer time setting method for bus transportation tasks. On this basis, we construct an optimization model, which is used for the joint optimal scheduling of EBs and CBs under different mixing rates. A heuristic procedure based on the genetic algorithm is designed to solve the model. The proposed methodology is validated based on data from Beijing Public Transport, China. The results show that the proposed model considering micro driving conditions is superior to the conventional model in terms of rationality and reliability.

Automated summary

This study proposes a joint optimal scheduling model for a mixed bus fleet under micro driving conditions, using estimation of bus trip time and buffer time setting methods to construct an optimization model for scheduling. A heuristic procedure based on the genetic algorithm is used to improve upon the conventional model.