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Valuing Factors Influencing Bicycle Route Choice Using a Stated-Preference Survey

机译:使用状态偏好调查影响自行车路线选择的重要因素

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This paper demonstrates a willingness-to-pay (WTP)-based approach to quantify a bicyclist's perception toward a few key attributes related to bicycle route choice. To check for city-specific influence on bicycle route choice, two small-sized Indian cities, Kharagpur and Asansol with different sociodemographic characteristics have been chosen. A stated-preference (SP) survey is designed to develop multinomial logit (MNL) and random parameter logit (RPL) models for a complete dataset. Additionally, heterogeneity around the means of random parameters is investigated in RPL models with respect to socioeconomic factors, such as income, motorized two-wheeler (TW) ownership, and user type (choice/captive). Subsequently, WTP estimates are derived for key determinants influencing bicycle route choice, namely, road width, level of risk, route visibility, and bicycle journey time. In general, RPL models are observed to be statistically superior and able to represent the behavioral data better than MNL models. Results reveal that level of risk (measure of safety) is perceived as the top most attribute influencing bicyclist's route choice irrespective of city characteristics, followed by route visibility and road width. Although modeled with income heterogeneity, bicycle journey time was the most valued bicycle journey time attribute among less-affluent users in Kharagpur. On the other hand, Asansol users valued bicycle journey time four to five times lesser and preferred safer routes than shorter routes. (C) 2017 American Society of Civil Engineers.
机译:本文演示了一种基于支付意愿(WTP)的方法,用于量化骑车人对与自行车路线选择相关的一些关键属性的看法。为了检查特定城市对自行车路线选择的影响,我们选择了两个具有不同社会人口学特征的小型印度城市,哈拉格布尔和阿桑索尔。陈述偏好(SP)调查旨在开发完整数据集的多项式logit(MNL)和随机参数logit(RPL)模型。此外,在RPL模型中针对社会经济因素(例如收入,机动两轮车(TW)所有权和用户类型(选择/专属))调查了随机参数均值周围的异质性。随后,就影响自行车路线选择的关键决定因素得出WTP估计值,即道路宽度,风险等级,路线可见性和自行车旅行时间。通常,与MNL模型相比,RPL模型在统计上是优越的,并且能够更好地表示行为数据。结果表明,无论城市特性如何,风险水平(安全性度量)被认为是影响骑车人的路线选择的最重要因素,其次是路线的可见性和道路宽度。尽管以收入异质性为模型,但自行车旅行时间是Kharagpur较不富裕的用户中最有价值的自行车旅行时间属性。另一方面,与短路线相比,Asansol用户认为自行车旅行时间少了四到五倍,更喜欢安全的路线。 (C)2017年美国土木工程师学会。

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