Time of day intervals partition for bus schedule using GPS data

被引:60
作者
Bie, Yiming [1 ]
Gong, Xiaolin [2 ]
Liu, Zhiyuan [2 ]
机构
[1] Harbin Inst Technol, Sch Transportat Sci & Engn, Harbin 150090, Peoples R China
[2] Southeast Univ, Sch Transportat, Nanjing 210096, Jiangsu, Peoples R China
基金
中国国家自然科学基金; 中国博士后科学基金;
关键词
Bus schedule; Time-of-day intervals; Partition algorithm; Historic GPS data; ROBUST OPTIMIZATION MODEL; TRANSIT NETWORK DESIGN; TRAVEL-TIME; DWELL TIME; FREQUENCY; ALGORITHM; SERVICE; ROUTES;
D O I
10.1016/j.trc.2015.09.016
中图分类号
U [交通运输];
学科分类号
08 ; 0823 ;
摘要
Time of day partition of bus operating hours is a prerequisite of bus schedule design. Reasonable partition plan is essential to improve the punctuality and level of service. In most mega cities, bus vehicles have been equipped with global positioning system (GPS) devices, which is convenient for transit agency to monitor bus operations. In this paper, a new algorithm is developed based on GPS data to partition bus operating hours into time of day intervals. Firstly, the impacts of passenger demand and network traffic state on bus operational performance are analyzed. Then bus dwell time at stops and inter-stop travel time, which can be attained based on GPS data, are selected as partition indexes. For buses clustered in the same time-of-day interval, threshold values of differences in dwell time at stops and inter-stop travel time are determined. The buses in the same time-of-day interval should have adjacent dispatching numbers, which is set as a constraint. Consequently, a partition algorithm with three steps is developed. Finally, a bus route in Suzhou China is taken as an example to validate the algorithm. Three partition schemes are given by setting different threshold values for the two partition indexes. The present scheme in practice is compared with the three proposed schemes. To balance the number of ToD intervals and partition precision, a Benefit Evaluation Index is proposed, for a better time-of-day interval plan. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码:443 / 456
页数:14
相关论文
共 29 条
[1]   Prediction Model of Bus Arrival Time at Signalized Intersection Using GPS Data [J].
Bie, Yiming ;
Wang, Dianhai ;
Qi, Hongsheng .
JOURNAL OF TRANSPORTATION ENGINEERING, 2012, 138 (01) :12-20
[3]   Bus dispatching at timed transfer transit stations using bus tracking technology [J].
Dessouky, M ;
Hall, R ;
Nowroozi, A ;
Mourikas, K .
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 1999, 7 (04) :187-208
[4]   Transit network design and scheduling: A global review [J].
Guihaire, Valerie ;
Hao, Jin-Kao .
TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE, 2008, 42 (10) :1251-1273
[5]   Identifying Time-of-Day Breakpoints Based on Nonintrusive Data Collection Platforms [J].
Guo, Rui ;
Zhang, Yu .
JOURNAL OF INTELLIGENT TRANSPORTATION SYSTEMS, 2014, 18 (02) :164-174
[6]   Determining optimal frequency and vehicle capacity for public transit routes: A generalized newsvendor model [J].
Herbon, Avi ;
Hadas, Yuval .
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL, 2015, 71 :85-99
[7]   DESIGN OF ROUTES SERVICE FREQUENCIES AND SCHEDULES FOR A MUNICIPAL BUS UNDERTAKING - A CASE STUDY [J].
LAMPKIN, W ;
SAALMANS, PD .
OPERATIONAL RESEARCH QUARTERLY, 1967, 18 (04) :375-&
[8]  
Li MT, 2006, TRANSPORT RES REC, P59
[9]  
Likas A, 2003, PATTERN RECOGN, V36, P451, DOI 10.1016/S0031-3203(02)00060-2
[10]   Bus stop-skipping scheme with random travel time [J].
Liu, Zhiyuan ;
Yan, Yadan ;
Qu, Xiaobo ;
Zhang, Yong .
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2013, 35 :46-56