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Evolution of latent modal captivity and mode choice patterns for commuting trips: A longitudinal analysis using repeated cross-sectional datasets

机译:通勤旅行的潜在模态囚禁和模式选择模式的演变:使用重复截面数据集的纵向分析

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This paper presents an investigation of the temporal evolution of commuting mode choice preference structures. It contributes to two specific modelling issues: latent modal captivity and working with multiple repeated crossectional datasets. In this paper latent modal captivity refers to captive reliance on a specific mode rather than all feasible modes. Three household travel survey datasets collected in the Greater Toronto and Hamilton Area (GTHA) over a ten-year time period are used for empirical modelling. Datasets collected in different years are pooled and separate year-specific scale parameters and coefficients of key variables are estimated for different years. The empirical model clearly explains that there have been significant changes in latent modal captivity and the mode choice preference structures for commuting in the GTHA. Changes have occurred in the unexplained component of latent captivities, in transportation cost perceptions, and in the scales of commuting mode choice preferences. The empirical model also demonstrates that pooling multiple repeated cross-sectional datasets is an efficient way of capturing behavioural changes over time. Application of the proposed mode choice model for practical policy analysis and forecasting will ensure accurate forecasting and an enhanced understanding of policy impacts.
机译:本文对通勤模式选择偏好结构的时间演变进行了研究。它导致了两个特定的建模问题:潜在的模态囚禁和使用多个重复的截面数据集。在本文中,潜在的模态囚禁是指对特定模式而非所有可行模式的囚禁依赖。在十年的时间段内,在大多伦多地区和汉密尔顿地区(GTHA)收集的三个家庭旅行调查数据集用于经验建模。汇总不同年份收集的数据集,并估算不同年份的不同年份特定规模参数和关键变量系数。该经验模型清楚地说明,在GTHA中,潜在的模态囚禁和通勤的模式选择偏好结构已发生了显着变化。潜在能力的无法解释的组成部分,运输成本感知以及通勤方式选择偏好的规模都发生了变化。该经验模型还表明,合并多个重复的横截面数据集是捕获随时间变化的行为的有效方法。将建议的模式选择模型应用于实际政策分析和预测将确保准确的预测并增强对政策影响的理解。

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