Journal of Guangxi Normal University(Natural Science Edition) ›› 2019, Vol. 37 ›› Issue (3): 9-20.doi: 10.16088/j.issn.1001-6600.2019.03.002

Previous Articles     Next Articles

Demand Responsive Transit Scheduling Method Considering Real-time Demand

HAN Bowen   

  1. Guangzhou Transport Planning Research Institute,Guangzhou Guangdong 510030, China
  • Online:2019-07-12 Published:2019-07-12

Abstract: The operation and scheduling of demand responsive transit is a complicated optimization control project. This paper mainly studies how to use the information conditions provided by the vehicle networking platform to study the scheduling method of demand responsive transit, so as to provide travelers with high-quality transportation services under the mode of both advance and real-time reservation. Firstly, the goal and method of dispatching are designed, then by balancing the benefits of both supply and demand, and fully considering the diversified travel needs of passengers, the static and dynamic scheduling models are established, which are obtained by genetic algorithm and precise algorithm respectively. Finally, two different types of vehicles are used to verify the effectiveness of the scheduling method and model proposed in this paper,the results show that the comprehensive benefit of the larger passenger-carrying vehicle is better, but the smaller passenger-carrying vehicle can better meet the passenger’s travel time requirements.

[1] 胡郁葱,陈栩罗,嘉陵. 多起终点多车型混载的定制公交线路规划模型[J].广西师范大学学报(自然科学版),2018,36(4):1-11.
[2] 郑汉张,星臣,王志美.混合车型需求响应公交服务定制问题研究[J].交通运输系统工程与信息,2018,18(2):157-163.
[3] 柳伍生,周向栋,贺剑,等. 基于多需求响应的定制公交绿色线网优化[J].公路交通科技,2018,35(3):132-142.
[4] PAN S, YU J, YANG X, et al. Designing a flexible feeder transit system serving lrregularly shaped and gated communities: determining service area and feeder route planning[J]. Journal of Urban Planning and Development, 2015,141(3):100-109.
[5] MALUCELLI F, NONATO M, PALLOTTINO S. Demand adaptive systems: some proposals on flexible transit1[M]//Operational research in industry. [s.l.]:Palgrave Macmillan, 1999: 157-182.
[6] NOURBAKHSH S M, OUYANG Y. A structured flexible transit system for low demand areas[J]. Transportation Research Part B Methodological, 2012, 46(1): 204-216.
[7] 潘述亮,卢小林,邹难. 灵活型接驳公交路径优化及协同调度模型[J]. 吉林大学学报(工学版), 2016,46(6): 1827-1835.
[8] 胡祥培, 吴丽荣. 低密度客流条件下柔性路径巴士实时调度的干扰管理模型[J]. 系统管理学报, 2012,21(6):811-818.
[9] 卢小林,潘述亮,邹难.复杂路网下灵活接驳公交路径优化研究[J]. 交通运输系统工程与信息, 2016,16(6):128-134.
[10]潘述亮, 俞洁, 邹难, 等. 含特殊需求的灵活接驳公交服务区域与路径选择[J]. 东北大学学报(自然科学版), 2014, 35(11): 1650-1654.
[11]龙哲竞,靳文舟,龚隽.需求响应公交接驳小车路径规划研究[J].交通科学与工程,2017,33(4):87-92.
[12]芒烈. 面向轨道交通站点的需求响应型接驳公交系统调度方法[D]. 长春: 吉林大学, 2017.
[13]高煦明. 固定站点需求响应式接驳公交调度模型研究[D]. 南京: 东南大学, 2015.
[14]邱丰,李文权,沈金星.可变线路式公交的两阶段车辆调度模型[J].东南大学学报(自然科学版),2014,44(5):1078-1084.
[15]王诗琪. 基于出行行为分析的灵活公交动态调度模型研究[D]. 北京: 北京交通大学, 2016.
[16]张文博,苏秦,程光路.基于动态需求的带时间窗的车辆路径问题[J].工业工程与管理,2016,21(6):68-74.
[17]谢昭瑞. 城乡公共客运服务运行模式及网络构建技术研究[D]. 南京: 东南大学, 2013.
[18]李仁安, 袁际军. 基于改进遗传算法的物流配送路线优化研究[J]. 武汉理工大学学报, 2004,12:99-101.
No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
[1] LI Yuhui, CHEN Zening, HUANG Zhonghao, ZHOU Qihai. Activity Time Budget of Assamese macaque (Macaca assamensis) during Rainy Season in Nonggang Nature Reserve, Guangxi, China[J]. Journal of Guangxi Normal University(Natural Science Edition), 2018, 36(3): 80 -86 .
[2] QIN Yingying, QI Guangchao, LIANG Shichu. Effects of Eichhornia crassipes Aqueous Extracts on Seed Germination of Ottelia acuminata var. jingxiensis[J]. Journal of Guangxi Normal University(Natural Science Edition), 2018, 36(3): 87 -92 .
[3] WEI Hongjin, ZHOU Xile, JIN Dongmei, YAN Yuehong. Additions to the Pteridophyte Flora of Hunan, China[J]. Journal of Guangxi Normal University(Natural Science Edition), 2018, 36(3): 101 -106 .
[4] BAO Jinping, ZHENG Lianbin, YU Keli, SONG Xue, TIAN Jinyuan, DONG Wenjing. Skinfold Thickness Characteristics of Yi Adults in Daliangshan,China[J]. Journal of Guangxi Normal University(Natural Science Edition), 2018, 36(3): 107 -112 .
[5] LIN Yongsheng, PEI Jianguo, ZOU Shengzhang, DU Yuchao, LU Li. Red Bed Karst and Its Hydrochemical Characteristics of Groundwater in the Downstream of Qingjiang River, China[J]. Journal of Guangxi Normal University(Natural Science Edition), 2018, 36(3): 113 -120 .
[6] ZHANG Ru, ZHANG Bei, REN Hongrui. Spatio-temporal Dynamics Analysis and Its Affecting Factors of Cropland Loss in Xuangang Mining Area, Shanxi, China[J]. Journal of Guangxi Normal University(Natural Science Edition), 2018, 36(3): 121 -132 .
[7] LI Xianjiang, SHI Shuqin, CAI Weimin, CAO Yuqing. Simulation of Land Use Change in Tianjin Binhai New Area Based on CA-Markov Model[J]. Journal of Guangxi Normal University(Natural Science Edition), 2018, 36(3): 133 -143 .
[8] WANG Mengfei, HUANG Song. Spatial Linkage of Tourism Economy of Cities in West River Economic Belt in Guangxi, China[J]. Journal of Guangxi Normal University(Natural Science Edition), 2018, 36(3): 144 -150 .
[9] LIU Guolun, SONG Shuxiang, CEN Mingcan, LI Guiqin, XIE Lina. Design of Bandwidth Tunable Band-Stop Filter[J]. Journal of Guangxi Normal University(Natural Science Edition), 2018, 36(3): 1 -8 .