华南理工大学学报（自然科学版）2025，Vol.53Issue(6)：77-90,14.DOI:10.12141/j.issn.1000-565X.240331
基于模型预测控制的需求响应公交动态调度
Dynamic Scheduling of Demand Responsive Transit Based on Model Predictive Control
摘要
Abstract
As a typical representative of the new mode of shared public transport,demand responsive transit(DRT)systems are facing the challenge of efficiently processing travel demand and real-time planning of vehicle routes.Traditional dynamic scheduling methods for DRT primarily focus on adjusting vehicle routes after demand has been realized,which often limits their ability to effectively respond to dynamic fluctuations in travel demand.Therefore,this study introduced a Model Predictive Control(MPC)approach and develops a dynamic scheduling model for DRT based on a multi-period rolling optimization framework.The model used potential future stage passenger flow information to optimize current stage scheduling decisions and timely re-planning according to the latest disclosed information to cope with the uncertainty and dynamic changes of demand.In terms of solution methods,this study integrated the adaptive large neighborhood search(ALNS)strategy to design the MPC-ALNS algorithm.It itera-tively optimized the vehicle scheduling sequence through a two-phase heuristic approach.Numerical experimental results demonstrate that in ideal scenarios without prediction deviation,compared to traditional dynamic scheduling methods,the proposed method significantly reduces the total cost of the system by 14.54%.Even in a pessimistic scenario with a 30%prediction deviation,it still achieves a cost optimization of 5.27%,and various passenger ser-vice indicators show superior performance,indicating strong universal applicability in different stochastic environ-ments.At the same time,the experiment further verified the stable optimization performance of the method in dealing with different orders and vehicle scales,and analyzed the sensitivity of the rejection cost and proposed the setting idea of the optimal rejection cost suitable for different operating scenarios.关键词
交通运输工程/需求响应公交/动态调度/模型预测控制/自适应大邻域搜索算法Key words
transportation engineering/demand responsive transit/dynamic scheduling/model predictive con-trol/adaptive large neighborhood search algorithm分类
交通工程引用本文复制引用
靳文舟,张永,孙洁..基于模型预测控制的需求响应公交动态调度[J].华南理工大学学报（自然科学版）,2025,53(6):77-90,14.基金项目
国家自然科学基金项目(52072128)Supported by the National Natural Science Foundation of China(52072128) （52072128）
