Providing insights into multi-day traveller behaviour to inform sustainable transport policies and practices

提供对多日旅行者行为的见解，为可持续交通政策和实践提供信息

• 批准号: ES/S010165/1
• 负责人: Fiona Crawford
• 金额: $ 10.25万
• 依托单位: University of the West of England
• 依托单位国家: 英国
• 项目类别: Fellowship
• 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=ES%2FS010165%2F1
• 关键词: Providing; insights; into; multi; day

A good understanding of traveller behaviour underpins all policies which are effective in influencing travel behaviour to reduce congestion, increase activity levels, improve air quality and/or reduce carbon emissions. It is also key in planning economically efficient transport systems with high levels of customer satisfaction. To encourage a more substantial change in behaviour which can be maintained over a longer period of time, it is essential to focus on people's travel behaviour over weeks and months, rather than focusing on a particular trip or a particular day only. My research takes this more holistic approach, enabling me to examine transport costs charged weekly, monthly or annually, and travel patterns in the context of broader societal changes, such as changing working patterns, and changing family dynamics. As described in the UK's Industrial Strategy (HM Government, 2017, p48), fundamental changes in transport systems will occur over the coming decade, for example due to the introduction of autonomous vehicles and a shift away from individual vehicle ownership. It is more important than ever that people's transport needs and travel behaviour inform appropriate public policy and a vision for a more sustainable future, rather than changes being primarly driven by profit-making.This research is timely due to the increasing importance of the data-driven economy, as emphasised within the Industrial Strategy (HM Government, 2017). For transport, large emerging data sources include smartcard and contactless bank card payments on local buses and data collected using mobile phone technologies. New methods are required to extract the relevant information from these data sources. During my PhD, I developed methodologies to gain insights into multi-day travel behaviour on the road network from large quantities of data collected continuously and passively. During the fellowship, I will collaborate closely with potential users of the methodologies I develop. I will adapt the methodologies for different contexts and gain experience in handling a wider variety of transport data, including public transport and multi-modal data. By working closely with Reading Buses, Bristol Traffic Control Centre and Living Streets, I will provide insights into the multi-day travel behaviour of their customers, and gain a better understanding of their current priorities and barriers to changing practices. I will produce tailored reports for each of these collaborators. I will pursue connections I have made, including with a private sector body providing non-emergency patient transfers and a private sector consultant. I will use this experience to develop freely accessible tools which can be used to apply the methodologies developed.The fellowship will enable me to take my research to the next level by examining the consequences of the insights learned from these new methodologies, for example the suitability of multi-day public transport fare structures. I have also identified that to apply my methods to data from large city regions in the future, I will need to develop skills for handling even larger datasets. I will therefore be undertaking structured training to fill this gap, namely modules on the Data Science and Analytics MSc at Cardiff University. During the year, I will also continue to learn from my colleagues at UWE, for example by developing skills in longitudinal data analysis with help from my mentor, Associate Professor Kiron Chatterjee, who is an expert in this field for transport.I will communicate the methodologies I have developed, the findings and their implications to a range of audiences regionally, nationally and internationally. This will include presentations to academics and practitioners, writing academic journal papers, utilising contacts within the Centre for Transport and Society at UWE, and less traditional mediums such as a blog entry.

对旅行者行为的良好理解是所有有效影响旅行行为的政策的基础，以减少拥堵，增加活动水平，改善空气质量和/或减少碳排放。它也是规划经济高效、客户满意度高的交通系统的关键。为了鼓励人们在行为上作出更大的改变，并能在较长时间内保持这种改变，我们必须集中注意人们在数周和数月内的旅行行为，而不是只注意某一次旅行或某一天。我的研究采取了这种更全面的方法，使我能够检查每周，每月或每年收取的交通费用，以及在更广泛的社会变化背景下的旅行模式，例如改变工作模式和改变家庭动态。正如英国工业战略（HM Government，2017，第48页）所述，未来十年，交通系统将发生根本性变化，例如，由于自动驾驶汽车的引入和个人车辆所有权的转变。人们的交通需求和出行行为比以往任何时候都更加重要，因为这有助于制定适当的公共政策，并为更可持续的未来提供愿景，而不是主要由利润驱动的变化。这项研究是及时的，因为数据驱动经济的重要性日益增加，正如工业战略（HM Government，2017）所强调的那样。在交通方面，大型新兴数据源包括当地公交车上的电子钱包和非接触式银行卡支付，以及使用移动的电话技术收集的数据。需要新的方法从这些数据源中提取相关信息。在我的博士学位期间，我开发了一种方法，从连续和被动收集的大量数据中深入了解道路网络上的多日出行行为。在研究期间，我将与我开发的方法的潜在用户密切合作。我将根据不同的情况调整方法，并在处理更广泛的交通数据方面积累经验，包括公共交通和多式联运数据。通过与阅读巴士、布里斯托交通控制中心和生活街密切合作，我将深入了解他们客户的多日旅行行为，并更好地了解他们目前的优先事项和改变做法的障碍。我将为每个合作者制作量身定制的报告。我将寻求我所建立的联系，包括与一个提供非紧急病人转移的私营部门机构和一名私营部门顾问建立联系。我将利用这一经验来开发可免费使用的工具，这些工具可以用于应用所开发的方法。奖学金将使我能够通过检查从这些新方法学中获得的见解的后果，将我的研究提升到一个新的水平，例如多日公共交通票价结构的适用性。我还发现，为了将来将我的方法应用于大城市地区的数据，我需要开发处理更大数据集的技能。因此，我将进行结构化的培训，以填补这一空白，即在数据科学和分析硕士模块在卡迪夫大学。在这一年里，我也将继续向UWE的同事学习，例如在我的导师Kiron Chatterjee副教授的帮助下，发展纵向数据分析的技能，他是交通领域的专家。我将向区域，国家和国际的一系列受众传达我开发的方法，研究结果及其影响。这将包括介绍给学者和从业人员，撰写学术期刊论文，利用交通与社会中心内的联系在UWE，和不太传统的媒介，如博客条目。

项目成果

Segmenting travellers based on day-to-day variability in work-related travel behaviour

• DOI: 10.1016/j.jtrangeo.2020.102765
• 发表时间: 2020-06-01
• 期刊: JOURNAL OF TRANSPORT GEOGRAPHY
• 影响因子: 6.1
• 作者: Crawford, Fiona

Challenging assumptions about traveller behaviour

关于旅行者行为的挑战性假设

• 发表时间: 2019
• 期刊: International Transportation
• 作者: Crawford, F.

International Encyclopedia of Transportation

• DOI: 10.1016/c2017-0-02313-3
• 发表时间: 2021

Analysing Spatial Intrapersonal Variability of Road Users Using Point-to-Point Sensor Data

• DOI: 10.1007/s11067-021-09539-4
• 发表时间: 2021-07
• 期刊: Networks and Spatial Economics
• 影响因子: 2.4
• 作者: Fiona Crawford;D. Watling;R. Connors