摘要
运用合作博弈理论的夏普利值算法模拟数据建立假设模型,利用MATLAB对假设模型分析求解和检验,确定此模型在行车调度上的可行性。运用夏普利值算法建立行车调度优化模型,对比模型性能结果表明:优化后的模型以详细分析车辆发车次数对运营的影响为前提,对行车时间加以准确的分析,基于大数据预测客流量,可针对不同时间、不同峰值的客流量需求,智能配置出全新行车调度方案,为智慧交通中优化行车调度提供参考。
A hypothesis model was established on the Shapley-value algorithm,examined and tested by MATLAB to determine its feasibility in vehicle scheduling,and then an optimized scheduling model was established on the Shapley-value algorithm.By comparing the model performance,it is shown that the optimized model made accurate analysis of the journey time based on analysis of the impact of the quantity of vehicle run on operation,and created intelligent vehicle schedules that accommodates passenger flow demands at different periods and peaks using traffic prediction of big data and is capable of a reference for the optimization of traffic scheduling in smart transportation.
作者
郑晓东
朱薇
ZHENG Xiaodong;ZHU Wei(School of Software Engineering,Xiamen University of Technology,Xiamen 361024,China)
出处
《厦门理工学院学报》
2018年第3期42-47,共6页
Journal of Xiamen University of Technology
关键词
夏普利值算法
行车调度模型
优化模型
大数据
客流量
Shapley value algorithm
vehicle scheduling model
optimized model
big data
passenger flow
