Multiline Transit Coordination at a Hub Based on Bus-arrival Time Prediction

doi:10.12005/orms.2015.0146

Abstract

Abstract: Due to the poor prediction of traditional scheduling model, a SVM-based prediction model is put forward to forecast the arrival time of public transport vehicles at the transfer station. Then a scheduling model aimed at reducing the total waiting time of passengers is constructed to dynamically coordinate the departure time at the transfer station. Genetic Algorithm is applied to solve the dynamic scheduling problem in this paper. Finally, this paper verifies the feasibility of the model and algorithm with the data of Shahekou station in Dalian city. And the results show that the scheduling method this paper proposed is superior to the traditional scheduling method.

Key words: transportation planning and management, bus dynamic vehicle scheduling, arrival time prediction, SVM(support vector machine)-based model, genetic algorithm

摘要： 针对传统调度模型预见性不强的弱点,提出一个基于支持向量机(SVM)的公交车辆到达枢纽时间的预测模型,基于该模型构建以所有乘客节约时间最大为目标的调度模型,动态协调公交车辆从枢纽的发车时间,并基于遗传算法对该模型进行求解。最后,我们以大连市沙河口火车站枢纽为实例,对该模型和算法的可行性进行了检验,结果显示,本文提出的调度方法优于传统调度策略。

关键词: 交通运输规划与管理, 公交动态车辆调度, 到达时间预测, SVM模型, 遗传算法

CLC Number:

U492

YU Bin, CUI Yao, CAI Wan-jun, MA Ning. Multiline Transit Coordination at a Hub Based on Bus-arrival Time Prediction[J]. Operations Research and Management Science, 2015, 24(4): 246-253.

于滨, 崔瑶, 蔡婉君, 马宁. 基于运行时间预测的枢纽内多线路协调调度研究[J]. 运筹与管理, 2015, 24(4): 246-253.

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