交通运输系统工程与信息 ›› 2009, Vol. 9 ›› Issue (3): 114-119 .

• 系统工程理论与方法 • 上一篇    下一篇

出行时间价值计算及应用研究

宗芳* 1;隽志才2,1;张慧永1;贾洪飞1   

  1. 1.吉林大学交通学院,长春 130025;2.上海交通大学 交通运输研究所,上海200052
  • 收稿日期:2008-11-17 修回日期:2009-02-14 出版日期:2009-06-25 发布日期:2009-06-25
  • 通讯作者: 宗芳
  • 作者简介:宗芳(1979-),女,吉林市长春市人,讲师,博士
  • 基金资助:

    教育部博士点基金-新教师基金(200801831088);国家自然科学基金资助项目(50878129)

Calculation and Application of Value of Travel Time

ZONG Fang1; JUAN Zhi-cai 2,1; ZHANG Hui-yong1; JIA Hong-fei1   

  1. 1. Transportation College, Jilin University, Changchun 130025, China; 2. Institute of Transportation Studies, Shanghai Jiaotong University, Shanghai 200052, China
  • Received:2008-11-17 Revised:2009-02-14 Online:2009-06-25 Published:2009-06-25
  • Contact: ZONG Fang

摘要: 传统的出行时间价值计算方法无法考虑出行者主观因素对出行时间价值判断的影响以及出行时间的利用效率问题。本文综合应用生产法、收入法及非集计Probit模型,引入节省时间利用系数,建立了出行时间价值计算综合模型,对传统方法做出改进;应用已建时间价值计算模型及佛山市南海区出行调查数据计算出行者的广义出行费用,进而建立了出行频率预测Logistic模型;根据出行频率预测及敏感性分析对南海区实施拥挤收费策略的可行性进行了评价。结果表明,改进的时间价值计算方法可以充分考虑出行者主观因素对其时间价值判断的影响,解决时间价值利用率问题,并且提高时间价值计算的准确率。已建方法可为出行行为分析、预测和交通需求管理策略评价提供理论支持。

关键词: 出行时间价值, 广义出行费用, 出行行为, 出行频率, 拥挤收费

Abstract: The traditional calculation method of VOT (value of time) does not consider the influence of individual factors on VOT and the time-saving utilization. Based on the Production method, the income method, and disaggregate Probit model, the paper develops a new calculation method of VOT by introducing the time-saving utilization coefficient. With the new method and the travel survey data in Nanhai, Foshan, the paper calculates traveler’s generalized travel cost and formulates a Logistic-based travel frequency forecasting model. According to the travel frequency forecasting and the sensitivity analysis, the paper evaluates the feasibility of the congestion pricing policy in Nanhai. The results indicate that the improved method, with consideration of the individual factors, can solve the problem of time-saving utilization and increase the accuracy of VOT calculation. Moreover, the improved method provides theoretical support for travel behavior analysis, travel demand forecasting, and transportation demand management policy evaluation.

Key words: time value, generalized travel cost, travel behavior, travel frequency, congestion pricing

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