Identification of cycle lane priorities based on observed and potential cyclist trips using GIS, the case of the Metropolitan Area of Mendoza, Argentina

IF 2.2
G. Barón
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引用次数: 0

Abstract

ABSTRACT In Latin America and developing countries, urban planners often lack sufficient data on cyclists’ modal share and profile to establish effective cycling lane networks. Mendoza, Argentina, is such a city. This research aimed to identify adequate locations for new cycle lanes by speculating on potential cycle trips from observed patterns of existing cyclists for a coherent demand-based network. The study proposed a novel, simple, cost-effective Geographic Information Systems model that uses spatial and human data and presents results cartographically for policymakers. Statistical analysis of observed bicycle trips enabled constructing a local profile of cyclists, from which ‘potential trips’ were speculated: trips made by other modes, but which could have been biked given their distance, duration, purpose, and the traveler’s age. Geo-referencing observed and potential trips to their ‘sub-zones’ of origin and destination produced a migratory synthesis map highlighting general flows and densities. Superimposing this on the current cycling infrastructure exposed the critical gaps. As a broader aim, this geomatic method is readily transferable to other developing world settings. Actions for Mendoza and broader applications are proposed, significant limitations discussed, and further research suggested, noting issues of gender equity and safety.
以阿根廷门多萨市区为例,基于观察到的和潜在的骑自行车者行程,利用GIS识别自行车道优先级
在拉丁美洲和发展中国家,城市规划者通常缺乏关于骑自行车者的交通方式和概况的足够数据,无法建立有效的自行车道网络。阿根廷的门多萨就是这样一个城市。这项研究的目的是通过观察现有骑自行车者的潜在出行模式,为一个连贯的以需求为基础的网络,来确定新的自行车道的适当位置。该研究提出了一种新颖、简单、具有成本效益的地理信息系统模型,该模型使用空间和人类数据,并将结果以制图方式呈现给决策者。对观察到的骑自行车旅行进行统计分析,可以构建骑车者的本地概况,从中推测“潜在旅行”:通过其他方式进行的旅行,但考虑到它们的距离、持续时间、目的和旅行者的年龄,这些旅行可能是骑车的。根据观察到的地理信息,以及前往出发地和目的地“子区域”的潜在行程,绘制了一幅迁徙综合图,突出了总体流量和密度。将其叠加在现有的自行车基础设施上,暴露了关键的差距。作为一个更广泛的目标,这种地理方法很容易转移到其他发展中国家。提出了门多萨的行动和更广泛的应用,讨论了重大的限制,并建议进一步的研究,注意到性别平等和安全问题。
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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CiteScore
1.80
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