首页> 外文OA文献 >A Methodology to Estimate Time Varying User Responses to Travel Time and Travel Time Reliability in a Road Pricing Environment
【2h】

A Methodology to Estimate Time Varying User Responses to Travel Time and Travel Time Reliability in a Road Pricing Environment

机译:在道路定价环境中估计时间变化的用户对旅行时间和旅行时间可靠性的响应的方法

摘要

Road pricing has emerged as an effective means of managing road traffic demand while simultaneously raising additional revenues to transportation agencies. Research on the factors that govern travel decisions has shown that user preferences may be a function of the demographic characteristics of the individuals and the perceived trip attributes. However, it is not clear what are the actual trip attributes considered in the travel decision- making process, how these attributes are perceived by travelers, and how the set of trip attributes change as a function of the time of the day or from day to day.In this study, operational Intelligent Transportation Systems (ITS) archives are mined and the aggregated preferences for a priced system are extracted at a fine time aggregation level for an extended number of days. The resulting information is related to corresponding time-varying trip attributes such as travel time, travel time reliability, charged toll, and other parameters. The time-varying user preferences and trip attributes are linked together by means of a binary choice model (Logit) with a linear utility function on trip attributes. The trip attributes weights in the utility function are then dynamically estimated for each time of day by means of an adaptive, limited-memory discrete Kalman filter (ALMF).The relationship between traveler choices and travel time is assessed using different rules to capture the logic that best represents the traveler perception and the effect of the real-time information on the observed preferences. The impact of travel time reliability on traveler choices is investigated considering its multiple definitions.It can be concluded based on the results that using the ALMF algorithm allows a robust estimation of time-varying weights in the utility function at fine time aggregation levels. The high correlations among the trip attributes severely constrain the simultaneous estimation of their weights in the utility function. Despite the data limitations, it is found that, the ALMF algorithm can provide stable estimates of the choice parameters for some periods of the day. Finally, it is found that the daily variation of the user sensitivities for different periods of the day resembles a well-defined normal distribution.
机译:道路定价已成为管理道路交通需求并同时为运输机构增加收入的有效手段。对决定出行决策的因素的研究表明,用户偏好可能是个人人口统计学特征和感知到的出行属性的函数。但是,尚不清楚在旅行决策过程中考虑的实际旅行属性是什么,旅行者如何看待这些属性,以及旅行属性集如何根据一天中的时间或每天的不同而变化。在这项研究中,将挖掘可操作的智能运输系统(ITS)档案,并在较长的时间内以良好的时间汇总级别提取定价系统的汇总偏好。所得信息与相应的随时间变化的出行属性有关,例如出行时间,出行时间可靠性,收费公路和其他参数。时变的用户偏好和行程属性通过二进制选择模型(Logit)链接在一起,该模型具有行程属性上的线性效用函数。然后通过自适应的有限内存离散卡尔曼滤波器(ALMF)每天动态评估效用函数中的出行属性权重。使用不同的规则来评估出行者选择与出行时间之间的关系,以捕捉逻辑最能代表旅行者的感知以及实时信息对观察到的偏好的影响。考虑到旅行时间可靠性对旅行者选择的多种定义,研究了旅行时间可靠性对旅行者选择的影响,可以基于结果得出结论,使用ALMF算法可以在精细的时间聚合级别上可靠地估计效用函数中的时变权重。行程属性之间的高度相关性严重限制了效用函数中同时权重的估计。尽管存在数据限制,但发现ALMF算法可以在一天的某些时段提供选择参数的稳定估计。最后,发现用户敏感度在一天中不同时段的每日变化类似于定义明确的正态分布。

著录项

  • 作者

    Alvarez Patricio A;

  • 作者单位
  • 年度 2012
  • 总页数
  • 原文格式 PDF
  • 正文语种
  • 中图分类
  • 入库时间 2022-08-20 21:11:30

相似文献

  • 外文文献
  • 中文文献
  • 专利

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号