自行车用户的路线选择行为:大赫尔辛基地区电动自行车的期望与现实

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引用次数: 0

摘要

电动脚踏助力自行车(电动自行车)是一种新兴技术,旨在通过在踩踏时安装电池供电的电机来提高自行车的骑行效率。要有效推广自行车运动,了解影响骑车人路线选择行为的因素至关重要。本研究在考虑自行车类型(即电动自行车和普通自行车)的基础上,调查了骑车人的个人路线选择行为。通过离散选择模型对在芬兰进行的陈述偏好(SP)调查收集的数据进行了分析,以比较电动自行车和普通自行车用户在路线选择行为上的差异。研究还比较了电动自行车和普通自行车用户的多项式和混合 Logit 模型的输出结果,以解决 SP 数据中误差相关性的影响。此外,本研究还采用分类方法,从路线选择行为的角度研究了使用电动自行车时预期行为变化与实际行为变化之间的差异,即预期与现实之间的差距。我们的研究结果强调了一些因素,这些因素始终促进普通自行车和电动自行车用户骑自行车,特别是与交通的互动少、交叉路口少以及存在分隔的自行车设施。此外,我们的研究结果还表明,SP 调查的设计很好地捕捉到了个人的偏好。因此,观察结果不存在严重的相关性,即误差可以假定为独立且相同的分布。此外,我们还表明,具有相似特征的普通自行车用户和电动自行车用户对电动自行车对其骑车习惯的影响并没有相似的看法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Bike users’ route choice behaviour: Expectations from electric bikes versus reality in Greater Helsinki

Electric pedal-assist bikes (e-bikes) are an emerging technology that aims to enhance cycling by incorporating battery-powered motors activated while pedalling. To promote cycling effectively, it is crucial to understand the factors that influence cyclists’ route choice behaviour. This study investigates individual route choice behaviour among cyclists, taking into account their bike type (i.e., e-bikes and regular bikes). Data collected through a stated preference (SP) survey in Finland is analysed using discrete choice models to compare the differences between e-bike and regular bike users’ route choice behaviour. The study also compares the outputs of multinomial and mixed Logit models for both e-bike and regular bike users to address the impact of error correlation in SP data. Furthermore, by employing a classification approach, the study examines the differences between the expected and actual behavioural changes upon using e-bikes, referred to as the expectation–reality gap, in terms of route choice behaviour. Our research findings highlight certain factors that consistently promote cycling among both regular bike and e-bike users, specifically, low interaction with traffic, fewer intersections, and the presence of separated bike facilities. Also, our findings imply that the SP survey is well-designed to capture the preferences of the individuals. Hence, the observations are not severely correlated, i.e., errors can be assumed to be independently and identically distributed. Furthermore, we show that regular bike and e-bike users with similar characteristics do not share similar beliefs regarding the effects of e-bikes on their cycling habits.

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