[1]陈 波,赵春剑.运输能力约束条件下的旅客出行选择Logit模型[J].长安大学学报(自然科学版),2024,44(2):115-122.[doi:10.19721/j.cnki.1671-8879.2024.02.011]
　CHEN Bo,ZHAO Chun-jian.Logit model for travel mode choice with traffic capacity constraints[J].Journal of Chang’an University (Natural Science Edition),2024,44(2):115-122.[doi:10.19721/j.cnki.1671-8879.2024.02.011]
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运输能力约束条件下的旅客出行选择Logit模型()
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长安大学学报（自然科学版）[ISSN:1006-6977/CN:61-1281/TN]

卷:
第44卷
期数:
2024年2期
页码:
115-122
栏目:
交通工程
出版日期:
2024-03-01

文章信息/Info

Title:
Logit model for travel mode choice with traffic capacity constraints
文章编号:
1671-8879(2024)02-0115-08
作者:
陈 波; 赵春剑
(长安大学 运输工程学院,陕西 西安 710064)
Author(s):
CHEN Bo;  ZHAO Chun-jian
(College of Transportation Engineering, Chang'an University, Xi'an 710064, Shaanxi, China)
关键词:
交通工程;  运输通道;  Logit模型;  运输能力;  惩罚因子
Keywords:
traffic engineering;  transportation corridor;  Logit model;  traffic capacity;  penalty factor
分类号:
U491.14
DOI:
10.19721/j.cnki.1671-8879.2024.02.011
文献标志码:
A
摘要:
为了提升旅客运输通道交通需求预测的准确性,针对现有旅客出行选择模型未充分考虑交通方式运输能力约束的不足,在深入分析旅客出行选择机理和运输能力约束机制的基础上,通过经典多项Logit(MNL)模型效用函数的优化设计,引入惩罚因子表征运输能力对旅客出行选择的约束,建立运输能力约束条件下的旅客出行选择Logit模型(约束MNL模型),并设计模型求解算法预测各交通方式的分担率。以西宝(西安—宝鸡)客运通道为对象进行实例分析,通过2种MNL模型预测结果的对比分析,验证约束MNL模型预测性能的优越性。研究结果表明:在旅客出行选择过程中,交通方式运输能力的约束具有普遍性,是有效交通需求预测不可忽略的重要因素,约束MNL模型考虑了运输能力对旅客出行选择的影响,更符合旅客出行选择的决策过程,从机理上为提升交通需求预测的准确性提供了可靠保障; 惩罚因子反映了运输能力约束对旅客出行选择的影响,代表了运输能力约束条件下运输服务质量的下降和旅客出行效用的损失; 通过惩罚因子的合理赋值,建立旅客出行选择概率重新分配机制,能有效模拟旅客出行方式的转换、控制旅客出行选择的概率; 与传统MNL模型相比,约束MNL模型表现出了更优异的预测性能,能始终将预测结果控制在由运输能力决定的分担率上限范围内,预测结果符合实际、科学有效,能够为旅客运输通道的网络布局优化、运输组织设计等提供可靠数据支持。
Abstract:
In order to improve the accuracy of traffic demand forecasting for passenger transportcorridors, addressing the shortcoming that the traffic capacity constraints are not adequatelyconsidered in the traditional passengers' mode choice models, the mechanism of passengers'mode choice and constraints from traffic capacity were deeply analyzed, and a penaltyfactor was introduced through the utility function optimization of the classical MNL model, tocharacterize the constraints of traffic capacity on passengers' mode choice, a constrainedMNL model was proposed, and the corresponding algorithm was designed to forecast the share ofeach transportation mode. The XiBao(Xi'an to Baoji)passenger corridor was taken as anexample to verify the superior performance of the constrained MNL model by comparativeanalyzing the forecasting results of the two models. The results show that in the process ofpassengers' mode choice, the constraints of traffic capacity are universal, which is an importantfactor that cannot be ignored for effective traffic demand forecasting, the constrained MNL modeltakes into account the impact of traffic capacity on passengers' mode choice, which is more in linewith the decision-making process of passengers' mode choice, and provides a reliable guaranteefor improving the accuracy of traffic demand forecasting from the mechanism. The penaltyfactor reflects the impact of traffic capacity constraints on passengers' mode choice, and representsthe decline in transportation service quality and the loss of passengers' utility. Through thereasonable assignment of the penalty factor, it can redistribute the passengers' choice probability,effectively simulate the shift of passengers' mode choice and control the probability ofpassengers' mode choice. Compare with the traditional MNL model, the constrained MNLmodel shows better performance, which can always control the forecasting results within theupper limit of the share determined by the traffic capacity, and the results are realistic, scientificand effective, which can provide reliable data support for the optimization of the network layoutand the design of the transportation organization.2 tabs, 6 figs, 30 refs.

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备注/Memo

备注/Memo:
收稿日期:2023-09-29
基金项目:教育部人文社会科学基金项目(20YJC790007); 陕西省社会科学基金项目(2019D013); 中央高校基本科研业务费专项资金项目(300102341677); 陕西省自然科学基金项目(2022JM-426)
作者简介:陈 波(1988-),男,陕西安康人,讲师,工学博士,E-mail:chb@chd.edu.cn。
更新日期/Last Update: 2024-03-01