考虑拥挤度的常规公交与地铁出行方式选择模型

doi:10.13229/j.cnki.jdxbgxb20191045

Abstract

Abstract:

In order to obtain the influence of crowding degree on the choice between two modes， the ground public transit and subway， this paper proposes a method to calculate the maximum crowding degree in the operating time. Passenger flow survey is conducted for 71 bus lines， metro line 1 and 3 by manual sampling survey in Harbin City. The maximum passenger number is observed and the crowding degree is calculated. Combining RP investigation with SP investigation， the corresponding relationship between the measured data of congestion degree and the congestion degree of passenger's subjective perception is established. The travel time， crowding degree and travel cost are graded in detail， and the situation of public transport travel choice is designed. The discrete Logit model is established. The results show that the crowding degree has the greatest influence on the public transit choice， the travel cost is the second， and the stroke time has the least impact.

Key words: public transportation, crowding degree, situation combination design, discrete selection model

CLC Number:

U491

Wen-hui ZHANG,Jia-qi QIN,Hong-tao LI,Hong-xing DENG,Guo-zhu CHENG. Travel choice model between bus transit and subway considering crowding degree[J].Journal of Jilin University(Engineering and Technology Edition), 2021, 51(1): 200-205.

Figures/Tables 8

Table 1

Results of bus crowding degree"

序号	公交路线i	最大断面乘客数n_B_i/人	拥挤度R_B
1	1路	47	0.59
2	2路	56	0.70
3	4路	37	0.46
$?$	$?$	$?$	$?$
69	219路	31	0.38
70	220路	31	0.39
71	223路	22	0.28

Table 1

Table 2

Fig.1

Table 3

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References 10

1	Pel A J, Bel N H, Pieters M. Including passengers' response to crowding in the Dutch national train passenger assignment model[J]. Transportation Research Part A: Policy and Practice, 2014, 66(1): 111-126.
2	Basu D, Hunt J D. Valuing of attributes influencing the attractiveness of suburban train service in Mumbai city: a stated preference approach[J]. Transportation Research Part A: Policy and Practice, 2012, 46(9): 1465-1476.
3	Kim K M, Hong S, Ko S, et al. Does crowding affect the path choice of metro passengers?[J]. Transportation Research Part A:Policy and Practice, 2015, 77: 292-304.
4	Tirachini A, Hensher D A, Rose J M. Multimodal pricing and optimal design of urban public transport: the interplay between traffic congestion and bus crowding[J]. Transportation Research Part B: Methodological, 2014, 61: 33-54.
5	Mahudin N D M, Cox T, Griffiths A. Measuring rail passenger crowding: scale development and psychometric properties[J]. Transportation Research Part F: Traffic Psychology and Behaviour, 2012, 15(1):38-51.
6	邵敏华, 李田野, 孙立军. 常规公交乘客对车内拥挤感知阻抗调查与建模[J]. 同济大学学报:自然科学版, 2012, 40(7): 1031-1034.
	Shao Min-hua, Li Tian-ye, Sun Li-jun. Survey method and model of passengers' cost perception of crowding level in bus[J]. Journal of Tongji University (Natural Science), 2012, 40(7): 1031-1034.
7	蒋盛川, 孙轶凡, 杜豫川. 拥挤度对公共交通方式选择意愿的影响[J]. 同济大学学报:自然科学版, 2012, 40(12): 1831-1835.
	Jiang Sheng-chuan, Sun Yi-fan, Du Yu-chuan. Influence of in-vehicle congestion degree on choice of public transit mode[J]. Journal of Tongji University (Natural Science), 2012, 40(12): 1831-1835.
8	高坤, 涂辉招, 李浩, 等. 出行者对不同交通方式行程时间可靠度和车内拥挤度的感知差异性[J]. 中国公路学报, 2017, 30(7): 126-133.
	Gao Kun, Tu Hui-zhao, Li Hao, et al. Travelers' perception differences in travel time reliability and crowding of mode-choice in multimodal networks[J]. China Journal of Highway and Transport, 2017, 30(7): 126-133.
9	霍月英, 李晓娟, 闫振英, 等. 基于乘客满意度的公交车站立乘客面积研究[J]. 交通运输系统工程与信息, 2019, 19(3): 157-162.
	Huo Yue-ying, Li Xiao-juan, Yan Zhen-ying, et al. Standing passenger space on a bus based on passenger satisfaction[J]. Journal of Transportation Systems Engineering and Information Technology, 2019, 19(3): 157-162.
10	王方, 陈金川, 张德欣. SP调查在交通方式选择模型中的应用[J]. 交通运输系统工程与信息, 2007, 7(5): 90-95.
	Wang Fang, Chen Jin-chuan, Zhang De-xin. Application of stated preference survey on traffic mode split model[J]. Journal of Transportation Systems Engineering and Information Technology, 2007, 7(5): 90-95.

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站点	乘客数/人						最大断面乘客数n_S_i/人	拥挤度R_S
站点	车厢1	车厢2	车厢3	车厢4	车厢5	车厢6	最大断面乘客数n_S_i/人	拥挤度R_S
黑龙江大学站	178	198	214	201	190	215	1196	0.83
和兴路站	251	240	222	218	215	212	1358	0.94
烟厂站	234	227	219	215	216	229	1340	0.93
哈西大街站	232	246	219	225	216	203	1341	0.93

观测值		预测值
		选择答案		正确百分比/%
		0	1	正确百分比/%
选择答案	0	1819	641	73.9
选择答案	1	679	3461	83.6
总体百分比				80

变量	回归系数B	标准差S.E.	观测值检验Wald	自由度df	显著性p	优势比Exp(B)
时间消耗	0.011	0.007	2.442	1	0.018	1.011
拥挤度	1.226	0.136	80.887	1	0.000	3.407
票价	-0.311	0.117	7.042	1	0.008	0.733
常量	0.105	0.131	0.646	1	0.422	1.111

Travel choice model between bus transit and subway considering crowding degree

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