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浙江大学学报(工学版)  2019, Vol. 53 Issue (2): 292-298    DOI: 10.3785/j.issn.1008-973X.2019.02.012
土木工程、交通工程     
乘客出行距离分布对轨道线网内公交竞争力的影响
张思佳1,2(),贾顺平1,2,*(),毛保华1,2,麻存瑞1,2,张桐1,2
1. 北京交通大学 城市交通复杂系统理论与技术教育部重点实验室,北京 100044
2. 北京交通大学 交通运输学院,北京 100044
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
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摘要:

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    
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 words: traffic engineering    trip distance    urban rail transit    choice probability of bus stop    passenger flow assignment    Logit-SUE
收稿日期: 2018-03-12 出版日期: 2019-02-21
CLC:  U 491  
通讯作者: 贾顺平     E-mail: 15114248@bjtu.edu.cn;shpjia@bjtu.edu.cn
作者简介: 张思佳(1991—),女,博士生,从事轨道交通与常规公交换乘衔接优化研究. orcid.org/0000-0002-9877-0577. E-mail: 15114248@bjtu.edu.cn
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引用本文:

张思佳,贾顺平,毛保华,麻存瑞,张桐. 乘客出行距离分布对轨道线网内公交竞争力的影响[J]. 浙江大学学报(工学版), 2019, 53(2): 292-298.

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.

链接本文:

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

图 1  长距离穿越式公交线路示意图
图 2  公交线路各站点客流OD矩阵
图 3  公交站点m的上、下行站点集合X、Y示意图
图 4  研究区域公交网络示意图
图 5  不同平均出行距离下的公交与轨道交通选择概率
图 6  公交线路站点选择概率和平均出行距离关系图
图 7  网络中点M位置示意图
图 8  研究区域内公交站点划分示意图
图 9  不同居住分散系数下的公交与轨道交通选择概率
图 10  公交线路站点选择概率和居住分散系数关系图
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.
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