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An investigation of commuting trip timing and mode choice in the Greater Toronto Area: Application of a joint discrete-continuous model

机译:大多伦多地区通勤出行时间和方式选择的研究:联合离散连续模型的应用

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摘要

The trip timing and mode choice are two critical decisions of individual commuters mostly define peak period traffic congestion in urban areas. Due to the increasing evidence in many North American cities that the duration of the congested peak travelling periods is expanding (peak spreading), it becomes necessary and natural to investigate these two commuting decisions jointly. In addition to being considered jointly with mode choice decisions, trip timing must also be modelled as a continuous variable in order to precisely capture peak spreading trends in a policy sensitive transportation demand model. However, in the literature to date, these two fundamental decisions have largely been treated separately or in some cases as integrated discrete decisions for joint investigation. In this paper, a discrete-continuous econometric model is used to investigate the joint decisions of trip timing and mode choice for commuting trips in the Greater Toronto Area (GTA). The joint model, with a multinomial logit model for mode choice and a continuous time hazard model for trip timing, allows for unrestricted correlation between the unobserved factors influencing these two decisions. Models are estimated by occupation groups using 2001 travel survey data for the GTA. Across all occupation groups, strong correlations between unobserved factors influencing mode choice and trip timing are found. Furthermore, the estimated model proves that it sufficiently captures the peak spreading phenomenon and is capable of being applied within the activity-based travel demand model framework.
机译:出行时间和模式选择是每个通勤者的两个关键决定,大多数决定了城市地区的高峰期交通拥堵。由于许多北美城市越来越多的证据表明拥堵高峰旅行时段的持续时间正在扩大(峰值扩展),因此有必要和自然地共同研究这两个通勤决策。除了与模式选择决策一起考虑外,还必须将行程时间建模为一个连续变量,以便在对政策敏感的交通需求模型中准确捕获峰值扩散趋势。但是,迄今为止,在这两个文献中,这两个基本决策在很大程度上被单独对待,或者在某些情况下被视为联合调查的综合离散决策。在本文中,离散连续经济模型用于研究大多伦多地区(GTA)的通勤出行时间和出行方式选择的联合决策。联合模型具有用于模式选择的多项式logit模型和用于行程定时的连续时间危害模型,可在影响这两个决策的未观察因素之间实现不受限制的相关性。这些模型是由职业团体使用2001年GTA的旅行调查数据估算得出的。在所有职业群体中,发现影响模式选择和行程时间的未观察因素之间具有很强的相关性。此外,估计的模型证明它可以充分捕获峰值扩散现象,并且能够在基于活动的旅行需求模型框架中应用。

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