Please wait a minute...
Journal of ZheJiang University (Engineering Science)  2019, Vol. 53 Issue (2): 292-298    DOI: 10.3785/j.issn.1008-973X.2019.02.012
Civil Engineering, Traffic Engineering     
Influence of passenger trip distance distribution on competitiveness of bus lines in urban rail transit network
Si-jia ZHANG1,2(),Shun-ping JIA1,2,*(),Bao-hua MAO1,2,Cun-rui MA1,2,Tong ZHANG1,2
1. MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology, Beijing Jiaotong University, Beijing 100044, China
2. School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China
Download: HTML     PDF(1187KB) HTML
Export: BibTeX | EndNote (RIS)      

Abstract  

The influence of trip distance distribution of passengers on the competitiveness of long bus lines was explored, from the perspective of continuous expansion of urban construction land. A calculation method to describe the choice probability of a bus stop was presented and a passenger flow assignment model based on Logit-SUE applied in the competitive public transit network was established. Then the influences of average passenger trip distance and residence dispersion coefficient on the choice probabilities of the bus line and the bus stops were explored. Results showed that average passenger trip distance had the trend of increasing with the continuous expansion of the city, and the competitiveness of long through-type bus lines decreased gradually since the urban rail transit was more suitable for long distance trips than the bus transit. The choice probability of each bus stop decreased as average passenger trip distance increased. The choice probabilities of the bus stops located in the center area of the line were less sensitive to the change of average passenger trip distance compared with that in the marginal area of the line. The expansion of the city led to the decrease of residence dispersion coefficient, and the competitiveness of long through-type bus line decreased accordingly. The choice probabilities of the bus stops decrease gradually with the distribution of passengers' residential locations changes from " small and scattered” to " large and concentrated”.



Key wordstraffic engineering      trip distance      urban rail transit      choice probability of bus stop      passenger flow assignment      Logit-SUE     
Received: 12 March 2018      Published: 21 February 2019
CLC:  U 491  
Corresponding Authors: Shun-ping JIA     E-mail: 15114248@bjtu.edu.cn;shpjia@bjtu.edu.cn
Cite this article:

Si-jia ZHANG,Shun-ping JIA,Bao-hua MAO,Cun-rui MA,Tong ZHANG. Influence of passenger trip distance distribution on competitiveness of bus lines in urban rail transit network. Journal of ZheJiang University (Engineering Science), 2019, 53(2): 292-298.

URL:

http://www.zjujournals.com/eng/10.3785/j.issn.1008-973X.2019.02.012     OR     http://www.zjujournals.com/eng/Y2019/V53/I2/292


乘客出行距离分布对轨道线网内公交竞争力的影响

从城市建设用地不断扩张的角度出发,研究城市居民出行距离分布变化对高密度轨道线网影响下的长距离穿越式公交线路竞争力的影响. 分析城市居民出行距离的变化趋势,提出公交站点选择概率的计算方法,建立基于Logit-SUE的公共交通网络客流分配模型,研究区域内居民平均出行距离和居住分散性系数对长距离穿越式公交线路竞争力及各站点选择概率的影响. 结果表明:在城市扩张趋势下,居民平均出行距离存在逐渐增大的趋势,轨道交通方式的优势逐渐突显,长距离穿越式公交线路竞争力逐渐减弱;公交线路各站点选择概率逐渐减小,且线路中心区站点对平均出行距离的灵敏性相对线路边缘区站点较低. 随着城市的不断扩张,居住分散性系数存在逐渐减小的趋势,分散性系数越小,居民居住地分布越集中,长距离穿越式公交线路的选择概率越小,竞争力越弱. 随着乘客居住地分布由“小而分散”向“大而集中”转变,长距离穿越式公交线路各站点选择概率存在逐渐减小的趋势.


关键词: 交通工程,  出行距离,  轨道交通,  站点选择概率,  客流分配,  Logit-SUE 
Fig.1 Diagram of long through-type bus line
Fig.2 OD matrix of through-type bus line
Fig.3 Sets X and Y of bus stops before and after bus stop m
Fig.4 Public transport network of study area
Fig.5 Choice probabilities of bus and urban rail transit with different average passenger trip distances
Fig.6 Relationship between choice probabilities of bus stops and average passenger trip distance
Fig.7 Position of M in network
Fig.8 Classification of bus stops in network
Fig.9 Choice probabilities of bus and urban rail transit with different residence dispersion coefficients
Fig.10 Relationship between choice probabilities of bus stops and residence dispersion coefficient
[1]   BIELLI M, CARAMIA M, CAROTENUTO P Genetic algorithms in bus network optimization[J]. Transportation Research Part C, 2002, 10 (1): 19- 34
doi: 10.1016/S0968-090X(00)00048-6
[2]   ZHAO C L, HUANG H J Modeling the equilibrium bus line choice behavior and transit system design with oblivious users[J]. Discrete Dynamics in Nature and Society, 2014, (2): 65- 83
[3]   CHU J C Mixed-integer programming model and branch-and-price-and-cut algorithm for urban bus network design and timetabling[J]. Transportation Research Part B: Methodological, 2018, 108: 188- 216
doi: 10.1016/j.trb.2017.12.013
[4]   DIJOSEPH P, CHIEN I J Optimizing sustainable feeder bus operation considering realistic networks and heterogeneous demand[J]. Journal of Advanced Transportation, 2013, 47 (5): 483- 497
doi: 10.1002/atr.v47.5
[5]   DENG L, GAO W, FU Y, et al Optimal design of the feeder-bus network based on the transfer system[J]. Discrete Dynamics in Nature and Society, 2013, (3): 1311- 1311
[6]   WONG H I Optimization of a feeder-bus route design by using a multiobjective programming approach[J]. Transportation Planning and Technology, 2014, 37 (5): 430- 449
[7]   孙杨, 孙小年, 孔庆峰, 等. 轨道交通新线投入运营下常规公交网络优化调整方法研究[J]. 铁道学报, 2014 (3): 1–8.
SUN Yang, SUN Xiao-nian, KONG Qing-feng, et al. Methodology of bus network optimization and adjustment under operation of new urban rail transit line [J]. Journal of the China Railway Society, 2014 (3): 1–8.
[8]   范海雁, 杨晓光, 夏晓梅, 等 基于轨道交通的常规公交线网调整方法[J]. 城市轨道交通研究, 2005, 8 (4): 36- 38
FAN Hai-yan, YANG Xiao-guang, XIA Xiao-mei, et al Bus line networks adjustment on rail transit basis[J]. Urban Mass Transit, 2005, 8 (4): 36- 38
doi: 10.3969/j.issn.1007-869X.2005.04.011
[9]   王振报, 陈艳艳, 段卫静. 常规公交线路调整方案评估方法[J]. 交通运输系统工程与信息, 2011, 11(3): 124–130.
WANG Zhen-bao, CHEN Yan-yan, DUAN Wei-jing. Evaluation method for lines adjustment scheme of bus in Beijing [J]. Journal of Transportation Systems Engineering and Information Technology, 2011, 11(3): 124–130.
[10]   寇伟彬, 陈旭梅. 面向城市布局形态的公交线网设计及其发展[J]. 哈尔滨工业大学学报, 2016, 48(9): 1–6.
KOU Wei-bin, CHEN Xu-mei. Transit network design based on the city layout and its development [J]. Journal of Harbin Institute of Technology, 2016, 48(9): 1–6.
[11]   李远, 四兵锋, 杨小宝, 等. 考虑换乘费用的城市公交网络随机用户均衡配流模型及算法[J]. 系统工程理论与实践, 2014(8): 2127–2134.
LI Yuan, SI Bing-feng, YANG Xiao-bao, et al. A stochastic user equilibrium model and algorithm for urban transit network with transfer cost [J]. Systems Engineering-Theory and Practice, 2014(8): 2127–2134.
[12]   李淑庆, 李哲, 朱文英 一体化公交网络均衡配流模型[J]. 交通运输工程学报, 2013, 13 (1): 62- 69
LI Shu-qing, LI Zhe, ZHU Wen-ying Equilibrium assignment model of integrated transit network[J]. Journal of Traffic and Transportation Engineering, 2013, 13 (1): 62- 69
doi: 10.3969/j.issn.1671-1637.2013.01.010
[13]   城市建设研究院. 城市公共交通分类标准: CJJ/T 114–2007 [S]. 北京: 中国建筑工业出版社, 2007: 2.
[14]   杨东赤, 任华玲, 四兵锋, 等. 基于时刻表的轨道交通网络动态配流模型研究[J]. 系统工程理论与实践, 2015, 35(5): 1214–1223.
YANG Dong-chi, REN Hua-ling, SI Bing-feng, et al. Research on schedule-based dynamic traffic assignment model for rail transit networks [J]. Systems Engineering-Theory and Practice, 2015, 35(5): 1214–1223.
[15]   胡晓伟, 王健, 孙广林 有限理性下出行者方式选择行为[J]. 哈尔滨工业大学学报, 2011, (12): 114- 118
HU Xiao-wei, WANG Jian, SUN Guang-lin Traveler’s mode choice behavior analysis under bounded rational[J]. Journal of Harbin Institute of Technology, 2011, (12): 114- 118
[16]   刘莎莎, 姚恩建, 张永生. 轨道交通乘客个性化出行路径规划算法[J]. 交通运输系统工程与信息, 2014, 14(5): 100–104.
LIU Sha-sha, YAO En-jian, ZHANG Yong-sheng. Personalized route planning algorithm for urban rail transit passengers [J]. Journal of Transportation Systems Engineering and Information Technology, 2014, 14(5): 100–104.
[1] Zhong-yu WANG,Ling WANG,Yan-li WANG,Bing WU. Traffic congestion prevention method during large-scale special events based on variable network topology optimization[J]. Journal of ZheJiang University (Engineering Science), 2021, 55(2): 358-366.
[2] Kai LU,Xin TIAN,Guan-rong LIN,Xing-dong DENG. Simultaneous optimization model of signal phase design and timing at intersection[J]. Journal of ZheJiang University (Engineering Science), 2020, 54(5): 921-930.
[3] Jia-qi ZENG,Dian-hai WANG. Improved numerical method for two-way arterial signal coordinate control[J]. Journal of ZheJiang University (Engineering Science), 2020, 54(12): 2386-2394.
[4] GONG Yue, LUO Xiao-Qin, WANG Dian-hai, YANG Shao-hui. Urban travel time prediction based on gradient boosting regression tress[J]. Journal of ZheJiang University (Engineering Science), 2018, 52(3): 453-460.
[5] SHANG Qiang, LIN Ci-yun, YANG Zhao-sheng, BING Qi-chun, XING Ru-ru. Traffic incident detection based on variable selection and kernel extreme learning machine[J]. Journal of ZheJiang University (Engineering Science), 2017, 51(7): 1339-1346.
[6] WANG Han qi, CHEN Hong, FENG Wei, LIU Wei wei. Multi-dimensional travel decision model of heterogeneous commuters based on Cumulative Prospect Theory[J]. Journal of ZheJiang University (Engineering Science), 2017, 51(2): 297-303.
[7] YU De-xin, TIAN Xiu-juan, YANG Zhao-sheng, ZHOU Xi-yang, CHENG Ze-yang. Improved arterial coordinated signal control optimization model[J]. Journal of ZheJiang University (Engineering Science), 2017, 51(10): 2019-2029.
[8] ZHOU Dan, MA Xiao long, JIN Sheng, WANG Dian hai. Modeling influencing factors of vehicle passing rate #br# in mixed bicycle traffic flow[J]. Journal of ZheJiang University (Engineering Science), 2015, 49(9): 1672-1678.
[9] SUN Wen-cai, YANG Zhi-fa, LI Shi-wu, XU Yi, GUO Meng-zhu, WEI Xue-xin. Driver fixation area division oriented DBSCAN-MMC method[J]. Journal of ZheJiang University (Engineering Science), 2015, 49(8): 1455-1461.
[10] LI Shi-wu, XU Yi, WANG Lin-hong, SUN Wen-cai, BIE Yi-ming. Gravitational search algorithm based adaptive low emission signal timing[J]. Journal of ZheJiang University (Engineering Science), 2015, 49(7): 1313-1318.