Computer Science ›› 2019, Vol. 46 ›› Issue (6A): 497-501.

• Big Data & Data Mining • Previous Articles     Next Articles

Bus Short-term Dynamic Dispatch Algorithm Based on Real-time GPS

ZHANG Shu-yu1, DONG Da1, XIE Bing1, LIU Kai-gui2   

  1. Beijing Institute of Aerospace Control Devices,Beijing 100094,China1;
    Guiyang Bus Transport Group Company,Guiyang 550081,China2
  • Online:2019-06-14 Published:2019-07-02

Abstract: This paper analyzed the limitation of traditional bus static dispatching.By using the real-time GPS data of online buses,and analyzing the bus operation mechanism under heavy traffic jam and sudden increase in passenger flow,this paper gave a new bus short-term dynamic dispatching algorithm based on neural network.Through simulations on bus lines in Guiyang,the proposed algorithm can efficiently solve the insufficient of traditional bus static dispatching,and reduce the interference of human factors in manual scheduling,which can realize the automation and intelligence of the bus dispatching.

Key words: GPS, Heuristic algorithm, Neural network, Public transport intelligence, Public transportation, Real-time dynamic dispatch, Static scheduling

CLC Number: 

  • TP312
[1]北京市公共交通总公司.运营调度管理 [M].北京:中国劳动出版社,1994.
[2]张飞舟,晏磊,范跃祖,等.智能交通系统中公交车辆动态调度研究 [J].公路交通科技,2002,19(3):123-126.
[3]CLARK G,WRIGHT J W.Scheduling of vehicles from a central deport to a number of delivery points [J].Computer & Operations Research,1994,32(12):568-581.
[4]陈芳.城市公交调度模型研究 [J].中南公路工程,2005,30(2):162-164.
[5]姚俊,吕智林,叶焉.基于满意度的公交调度模型研究 [J].交通信息与安全,2009,27(4):67-69.
[6]任传祥,郇宜军,尹唱唱.基于遗传禁忌搜索算法的公交调度研究[J].山东科技大学学报自然科学版,2008,27(4):53-56.
[7]刘鑫,何世伟.基于随机机会规划的公交调度模型研究 [J].交通标准化,2006(12):152-155.
[8]杨磊,刘卫鹏,周磊.基于改进的随机公交调度问题的数学模型 [J].河北工业大学学报,2009,39(1):74-78.
[9]宋瑞,赵航.基于机会约束的公交调度研究[J].数学的实践与认识,2005,35(1):89-95.
[10]刘志强,张利,吕学,等.基于离散Hopfield 神经网络的公交调度评价方法研究 [J].交通运输系统工程与信息,2011,11(2):77-83.
[11]林叶倩,李文权,邱丰,等.可变线路式公交车辆调度优化模型 [J].交通信息与安全,2012,30(5):14-18.
[12]童刚.遗传算法在公交调度中的应用研究[J].计算机工程,2005,31(13):29-31.
[13]郑小花,陈淑燕,武林芝.模拟退火算法在公交调度中的应用[J].信息化研究,2009,35(9):45-48.
[14]马永杰,云文霞.遗传算法研究进展[J].计算机应用研究,2012,9(4),1204-1205.
[15]SRINIVAS M,PATNAIK L.Adaptive probabilities of crossover and mutation in genetic algorithms[J].IEEE Transactions on System,Man and Cybernetics,1994,24(4):656-667.
[16]KHACHATURYAN A G,SEMENOVSKAYA S V,VAINSHTEIN B K.Statistical-thermodynamic approach to determination of structure amplitude phases[J].Kristallografiya,1979,24(5):519-524.
[17]MATYAS J.Random optimization [J].Automation and Remote Control,1965,26(2):246-253.
[18]BERREBI S J,WATKINS K E,LAVAL J A.A real-time bus dispatching policy to minimize passenger wait on a high frequency route [J].Transportation Research Part B,2015,81:377-389.
[19]YU B,WANG K M,PENG Z X,et al.Dynamic extra buses scheduling strategy in public transportation [J].Promet-Tranffic &Transportation,2015,27(3):205-216.
[20]GAO J,DENG W,JI Y J.Short term public transit dispatch model using state space neural networkes[J].Second International Conference on Intelligent Computation Technology and Automation,2009.
[21]RUMELHART D E,HINTON G E,WILLIAMS R J.Learning representations by back-propagating errors[J].Nature,1986,323(6088):533-536.
[22]王亮洁,胡大伟,董皓,等.物联网技术在航天安全生产管理系统中的应用[J].导航与控制,2016(4):108-112.
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