交通运输系统工程与信息 ›› 2013, Vol. 13 ›› Issue (4): 171-175.

• 系统工程理论与方法 • 上一篇    下一篇

燃油价格影响下的居民出行选择行为特征分析及建模

王京元*1, 韩艳2,赵建军3   

  1. 1. 深圳大学 土木工程学院,广东 深圳 518060; 2. 深圳市都市交通规划设计研究院有限公司, 广东 深圳 518054;3. 澳门科技大学 行政与管理学院
  • 收稿日期:2012-11-26 修回日期:2013-04-26 出版日期:2013-08-26 发布日期:2013-09-05
  • 作者简介:王京元(1977-), 男, 山东淄博人, 副教授, 工学博士.
  • 基金资助:

    国家自然科学基金资助项目(50908150, 51068013,51208307); 深圳市基础研究计划 (JC201005280483A, JC200903130302A).

Analysis and Model of Travel Choice Behavior with Influence of Fuel Prices

WANG Jing-yuan1, HAN Yan2,ZHAO Jian-jun3   

  1. 1.College of Civil Engineering, Shenzhen University, Shenzhen 518060, Guangdong China; 2. Shenzhen Metropolitian Transportation Planning & Design Institute, Shenzhen 518054, Guangdong, China; 3. Fanagement and Administratiion, Macau University of Science and Technology, China
  • Received:2012-11-26 Revised:2013-04-26 Online:2013-08-26 Published:2013-09-05

摘要:

采用意向调查与行为模型分析相结合的方法,量化研究油价影响下我国居民的出行行为特征,识别典型响应行为,筛选显著影响因素,建立居民出行方式选择模型.结果表明,油价上涨将影响大部分潜在购车者的购车意向,改变其购车计划;油价对小汽车出行者的影响更加显著,减少用车频率、避免高峰出行、改变出行方式是私家车主应对油价上涨的最常用措施;以地铁为代表的公共交通是首选的替代出行方式,经济状况、家庭结构等在很大程度上决定了出行者对小汽车的依赖程度.通过燃油税对油价进行调节,将对我国城市交通结构的优化、交通状况的改善起到关键作用;建议在实施过程中,充分考虑油价对不同居民的影响特点,提高实施效果.该研究可为我国交通需求管理策略的制定提供参考.

关键词: 城市交通, 出行行为, BNL模型, 燃油价格, 燃油税, 出行方式

Abstract:

This paper investigates the impacts of fuel price on household travel behaviors based on the stated preference survey and behavior model analysis. It aims to identify household’s responding behavior, key responding factors, and then formulates the household’s travel choice model. The results show that the rise of oil price exerts impacts on the purchasing intention of most potential car buyers. In addition, private car travelers are more sensitive to the fluctuations of oil prices. Reducing the frequency of car using, avoiding traveling during the peak hours, and changing travel mode are the most frequent options in response to increasing oil price. Particularly, the subway related mass transport is the first choice of alternative travel mode. Furthermore, it reveals that the degree of dependence on private car is largely determined by the household’s income and family structure. This study provides theoretical supports and useful implications for formulating traffic demand management strategies. It is suggested to regulate the oil price according to the fuel tax. Moreover, the differences of resident characteristics should be fully considered in the real implementation.

Key words: urban traffic, travel behavior, BNL model, fuel prices, fuel tax, travel mode

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