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

对旅行者行为的良好理解是有效影响旅行行为以减少拥堵、增加活动水平、改善空气质量和/或减少碳排放的所有政策的基础。它也是规划经济高效、客户满意度高的运输系统的关键。为了鼓励人们的行为发生更大的变化，并在更长的一段时间内保持下去，至关重要的是关注人们在几周和几个月内的旅行行为，而不是只关注特定的旅行或特定的一天。我的研究采用了这种更全面的方法，使我能够在更广泛的社会变化的背景下，检查每周、每月或每年收取的交通费用，以及出行模式，例如改变工作模式和改变家庭动态。正如英国的产业战略(英国政府，2017，第48页)所描述的那样，交通系统将在未来十年发生根本性变化，例如，由于自动驾驶汽车的引入和从个人拥有汽车的转变。人们的交通需求和出行行为为适当的公共政策和对更可持续的未来的愿景提供了比以往任何时候都更重要的信息，而不是主要由盈利驱动的变化。这项研究是及时的，因为数据驱动的经济越来越重要，正如产业战略(HM政府，2017)所强调的那样。在交通方面，大型新兴数据来源包括当地公交车上的智能卡和非接触式银行卡支付，以及使用移动电话技术收集的数据。从这些数据源中提取相关信息需要新的方法。在我的博士学位期间，我开发了一些方法，从持续和被动收集的大量数据中深入了解公路网上的多日出行行为。在团契期间，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，并在处理更广泛的运输数据方面积累经验，包括公共交通和多式联运数据。通过与雷丁巴士、布里斯托尔交通控制中心和Living Street的密切合作，我将深入了解他们客户的多日出行行为，并更好地了解他们目前的优先事项和改变做法的障碍。我将为这些合作者中的每一个制作量身定制的报告。我将继续与我建立的联系，包括与提供非紧急病人转送服务的私营部门机构和私营部门顾问建立联系。我将利用这一经验开发可免费使用的工具，用于应用所开发的方法。研究金将使我能够通过研究从这些新方法中学到的见解的后果，将我的研究提升到一个新的水平，例如多日公共交通收费结构的适用性。我还认识到，要将我的方法应用于未来来自大城市地区的数据，我将需要培养处理更大数据集的技能。因此，我将接受有组织的培训，以填补这一空白，即卡迪夫大学数据科学和分析硕士模块。在这一年里，我还将继续向我在威斯康星州大学的同事学习，例如，在我的导师、运输领域专家KIron Chatterjee副教授的帮助下发展纵向数据分析的技能。我将向地区、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。这将包括向学者和从业人员发表演讲，撰写学术期刊论文，利用威斯康星大学运输和社会中心内的联系人，以及不太传统的媒介，如博客条目。

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.