基于居民出行行为分析的公交线路调度研究

计算机科学 ›› 2014, Vol. 41 ›› Issue (Z6): 94-97.

基于居民出行行为分析的公交线路调度研究

李章维,郭冰冰,明洁,张贵军

浙江工业大学信息工程学院杭州310023;浙江工业大学信息工程学院杭州310023;浙江工业大学信息工程学院杭州310023;浙江工业大学信息工程学院杭州310023

出版日期:2018-11-14 发布日期:2018-11-14
基金资助:
本文受国家自然科学基金(61075062),浙江省自然基金(LY13F030008,Y1100891),国家大学生创新计划项目(201210337033),杭州市产学研合作项目(20131631E31),浙江工业大学重中之重学科开放基金(20120811)资助

Bus Line Scheduling Research Based on Residents’ Travel Behavior Analysis

LI Zhang-wei,GUO Bing-bing,MING Jie and ZHANG Gui-jun

Online:2018-11-14 Published:2018-11-14

摘要/Abstract

摘要： 针对居民出行高峰时段的交通拥堵问题,建立了以居民的出行行为分析为基础的公交线路调度模型。该模型运用生存分析理论对居民出行时间的影响因素进行分析,科学划分城市居民出行时段区间,进而针对该地区高峰时段的公交发车间隔构造非线性规划模型函数。模型函数综合考虑乘客时间成本和公交公司运营成本,加入权重系数并利用粒子群算法求解,从而得到最佳发车间隔时间。结合杭州某地区市民出行数据,通过实证研究得出优化后的调度时刻表,验证了模型的可行性和有效性。

关键词: 出行行为,生存分析理论,公交线路调度,发车间隔,粒子群算法中图法分类号TP301文献标识码A

Abstract: On a city bus for residents travel peak pressure,we established the bus line scheduling model which is mainly based on residents' travel behavior analysis．The model uses survival analysis theory to analyze the influence factors of residents travel time,find out the urban residents travel time interval science tumble,and construct nonlinear programming model function on bus headway of the peak time in the region．Model function includes the time cost of passengers and the bus company operating costs,introduces weighting factor,and uses particle swarm algorithm to get the best grid interval．On the basis of Hangzhou citizens travel data in a given area,the article derived optimized scheduling schedule from empirical studies,verified the feasibility and validity of the model.

Key words: Travel behavior,Survival analysis theory,Bus dispatching,Departure interval,Particle swarm optimization

李章维,郭冰冰,明洁,张贵军. 基于居民出行行为分析的公交线路调度研究[J]. 计算机科学, 2014, 41(Z6): 94-97. https://doi.org/

LI Zhang-wei,GUO Bing-bing,MING Jie and ZHANG Gui-jun. Bus Line Scheduling Research Based on Residents’ Travel Behavior Analysis[J]. Computer Science, 2014, 41(Z6): 94-97. https://doi.org/

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