基于贝叶斯网的城市迁居者通勤方式变迁模型

交通运输系统工程与信息 ›› 2017, Vol. 17 ›› Issue (6): 94-100.

基于贝叶斯网的城市迁居者通勤方式变迁模型

吴静娴，杨敏*

东南大学交通学院，南京210096

收稿日期:2017-04-19 修回日期:2017-08-05 出版日期:2017-12-25 发布日期:2017-12-25
作者简介:吴静娴（1987-），女，江苏盐城人，博士生.
基金资助:
国家自然科学基金/National Natural Science Foundation of China (51378120，51338003).

Commuting Modal Shift of Relocated Residents in City Based on Bayesian Networks

WU Jing-xian, YANG Min

School of Transportation, Southeast University, Nanjing 210096, China

Received:2017-04-19 Revised:2017-08-05 Online:2017-12-25 Published:2017-12-25

摘要/Abstract

摘要：

随着中国城市空间布局的扩展与郊区化现象的加剧，城市内部居住迁移导致居民出行交通结构发生演变.国内关于迁居—出行行为的研究主要集中于对迁居人群机动化通勤趋势及变化成因的宏观描述上，从微观角度分析城市内部迁居人群通勤方式转变的研究尚为少见.本文以南京为例，构建基于贝叶斯网络的迁居人群通勤方式转移模型，模拟并分析个人家庭信息、迁居属性，以及小区建成环境感知变化对原非机动(步行、自行车或电动车)通勤人群出行方式转移的影响.结果表明：家庭汽车、个人收入、新车的购置、住房类型、购房方式、迁居类型、地铁通勤便捷度和地铁步站距离是影响原非机动通勤人群转向小汽车出行的主要因素.研究结果可为城市规划者制定迁居通勤机动化的建成环境调控政策提供一定科学依据.

关键词: 交通工程, 居住迁移, 出行行为, 方式变迁, 贝叶斯网络

Abstract:

Triggered by rapid urban expansion and suburbanization in China, a great change has occurred in the commute pattern among relocated residents. Currently, studies on the mechanism between relocation and travel behavior undertaken in China mainly focus on describing the motorizing trend of movers’ commute behavior and explaining its possible causes in a regional or national level, but few have made an elaborate analysis from the personal aspect. Therefore, this paper is empirically made in Nanjing and a Bayesian network is developed to assess the impacts of movers’socio- demographic characteristics, relocation- related attributes and perceived changes in built environment on this modal shift. The inference results indicate that car ownership, personal income, additional car purchase, house type, house payment, relocation type, convenience of subway commuting, and distance to subway station are the most important determinants that lead to the commute modal shift towards private car. The result provides supportive insights for urban planner in countermeasure design on built environment to effectively control this motorizing trend.

Key words: traffic engineering, residential relocation, travel behavior, mode shift, Bayesian networks

中图分类号:

U491.1

吴静娴，杨敏. 基于贝叶斯网的城市迁居者通勤方式变迁模型[J]. 交通运输系统工程与信息, 2017, 17(6): 94-100.

WU Jing-xian, YANG Min. Commuting Modal Shift of Relocated Residents in City Based on Bayesian Networks[J]. Journal of Transportation Systems Engineering and Information Technology, 2017, 17(6): 94-100.

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链接本文: http://www.tseit.org.cn/CN/abstract/abstract19525.shtml

http://www.tseit.org.cn/CN/Y2017/V17/I6/94

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