Modelling the impact of road infrastructure on cycling moving speed

Afshin Jafari , Dhirendra Singh , Lucy Gunn , Alan Both , Billie Giles-Corti
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Abstract

Cycling for transport is a sustainable alternative to using motorised vehicles for daily trips and is a key form of micromobility. Travel time is a critical factor influencing cycling route choice behaviour and uptake. Thus, it is important to understand the factors affecting cycling travel time and speed and their impact on cycling behaviour. In this study, an agent-based transport simulation model with heterogeneous cycling speeds was developed and used for Melbourne to study the impact of a hypothetical traffic signal optimisation intervention along six key cycling corridors. Linear regression and random forest models were used to identify factors affecting cycling speed, which informed the parameters of the agent-based model. Simulation outputs showed, on average, an increase of 4.1 % in the number of cyclists on the corridors, as existing cyclists chose to use these corridors, and an average reduction in cyclists’ moving travel time of 6.2 % for those using the intervention corridors (excluding time spent waiting at traffic signals). The findings provide insights into the effects of road attributes on cycling speed and behaviour, as well as the effectiveness of interventions aimed at reducing cycling delays. These insights are valuable for developing solutions to optimise urban infrastructure for micromobility, enhancing the efficiency and appeal of cycling as a viable transport option.
模拟道路基础设施对自行车运动速度的影响
骑自行车作为交通工具是一种可持续的替代使用机动车辆进行日常旅行,是一种关键的微型交通形式。出行时间是影响骑行路线选择行为和吸收的关键因素。因此,了解影响骑行时间和速度的因素及其对骑行行为的影响是很重要的。在本研究中,我们开发了一个基于agent的、具有不同骑行速度的交通模拟模型,并以墨尔本为例,研究了假设的交通信号优化干预对六个关键骑行通道的影响。采用线性回归和随机森林模型识别影响循环速度的因素,从而为基于智能体的模型的参数提供信息。模拟结果显示,由于现有的骑自行车者选择使用这些走廊,骑自行车的人数平均增加了4.1 %,而使用干预走廊的骑自行车者的移动旅行时间平均减少了6.2 %(不包括等待交通信号的时间)。这些发现为了解道路属性对骑行速度和行为的影响,以及旨在减少骑行延误的干预措施的有效性提供了见解。这些见解对于开发优化城市微交通基础设施的解决方案,提高自行车作为一种可行的交通选择的效率和吸引力具有重要价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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