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New methods of space-time data analysis to operationalise passively collected transport data on the route network

时空数据分析的新方法可操作在路线网络上被动收集的运输数据

基本信息

批准号：
2106782
负责人：
金额：
--
依托单位：
University of Leeds
依托单位国家：
英国
项目类别：
Studentship
财政年份：
2018
资助国家：
英国
起止时间：
2018 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=studentship-2106782
关键词：
New methods space time data

项目摘要

Cycling has the potential to tackle multiple interrelated problems including sedentary lifestyles and the associated obesity crisis, air pollution and road traffic congestion. In recognition of its benefits for the environment, society and economy, Government aims to double cycling by 2025 (Department for Transport 2017).To do so depends on a number of interventions, including investment in safe, convenient and joined up cycling networks. A growing evidence-base demonstrates how this can happen. The Propensity to Cycle Tool (PCT) and Cycling Infrastructure Toolkit (CyIPT) projects, key components of which were developed at the University of Leeds, operationalise this data, providing a vital tool for local authorities and other stakeholders investing in cycling (Lovelace et al. 2017). However, a problem with these tools is that they take little account of the quality of existing infrastructure. Specifically, road and cycleway smoothness and width are absent from both projects.To overcome this problem new datasets are needed. The aim of the PhD will be to incorporate emerging datasets - such as those generated by See.Sense products - into transport planning, using new and innovative methods and new and emerging software for data science where appropriate.

骑自行车有可能解决多个相互关联的问题，包括久坐的生活方式和相关的肥胖危机，空气污染和道路交通拥堵。认识到自行车对环境、社会和经济的好处，政府的目标是到2025年将自行车数量增加一倍（交通部，2017年）。要做到这一点，需要采取一系列干预措施，包括投资于安全、方便和连接的自行车网络。越来越多的证据表明这是如何发生的。自行车倾向工具（PCT）和自行车基础设施工具包（CyIPT）项目的关键组成部分是在利兹大学开发的，可操作这些数据，为地方当局和其他投资自行车的利益相关者提供重要工具（Lovelace等人，2017年）。然而，这些工具的一个问题是，它们很少考虑现有基础设施的质量。具体来说，两个项目都缺少道路和自行车道的平滑度和宽度。为了克服这个问题，需要新的数据集。博士学位的目标是将新兴数据集（例如See.Sense产品生成的数据集）纳入交通规划，在适当的情况下使用新的创新方法以及新的新兴数据科学软件。