Modelling the Diverse Implications of Autonomous Mobility at the City Scale

城市交通系统的自动化有可能对人类的城市体验产生重大影响。自动驾驶汽车（AV）--从私人汽车到共享出租车和公共汽车--有望提高交通效率和道路安全，但也引发了有关其对城市领域的影响以及人车互动性质变化的问题。此外，全自动移动系统的实施还带来了与接入、设计和车辆所有权有关的政策挑战。该博士项目将采用基于代理的建模（ABM）来探索自动驾驶汽车在城市规模上的空间，社会和政策影响。研究的第一阶段将是定义一组自主移动性的场景。自动驾驶汽车的性质意味着这些场景可能从传统的观点到相当激进的城市交通新愿景。该项目将讨论这些不同的规划和政策方案如何体现在城市的不同结果中。场景空间可能包括以下内容，但将在研究的第一年更正式地勾勒出来：-车辆所有权模型（例如共享，个人）。自主多模式混合，包括整合和隔离的不同愿景，以及未来模式的作用（例如个人航空）。多模式、集成的票务和支付系统（即移动即服务）。对车辆使用的限制和定价可以按区域、按模式或其他方式应用。针对特定人群的政策措施。博士学位的第二个基础主题将是一套评估措施，以捕捉自动驾驶汽车对城市系统和社会的影响。在这一阶段，必须考虑自主流动对既定社会制度的广泛影响。同样，我们对这些影响的传统和激进观点都感兴趣。关于上述不同的系统配置，这些影响可能包括：-空间流量，交通密度和停车需求的变化。按人口特征（如按人口群体、贫困人口）区分的服务绩效和旅行时间的变化。车辆排放和环境负担的转移。移动系统变化带来的不同地点，服务和机会（例如健康，教育，商业）的可访问性变化。这些流动性模型将使用基于主体的建模来构建，这将使我们能够在精细的空间和人口尺度上探索各种情景。在ABM的框架内，我们将与利益相关者合作，探索政策和城市设计解决方案，旨在最大限度地提高城市及其公民的自主交通利益。通过建立城市规模的移动ABM，针对固有计算挑战的创新解决方案也有望成为研究的成果。博士项目将与地理学院，交通研究所和利兹数据分析研究所（利达）正在进行的基于代理的建模，城市分析和未来移动性的大量研究相结合并从中受益。

The automation of urban transportation systems has the potential to significantly impact the human experience of cities. Autonomous vehicles (AVs) - from private cars, to shared taxis, and buses - promise improved traffic efficiency and road safety yet raise questions around their effect on the urban realm and the changing nature of human-vehicle interaction. The implementation of wholly autonomous mobility systems furthermore presents policy challenges in relation to access, design, and vehicle ownership. This PhD project will take on these broader implications of autonomous mobility, using agent-based modelling (ABM) to explore the spatial, social, and policy implications of AVs at the urban scale. The first phase of the research will be to define a set of scenarios for autonomous mobility. The nature of AVs means these scenarios might range from conventional perspectives to quite radical new visions on urban mobility. This project will address how these different planning and policy scenarios might manifest in different outcomes for the city. The scenarios space might include the following, but will be more formally sketched out during the first year of study:- Vehicle ownership models (e.g. shared, personal).- Autonomous multimodal mix, including different visions for integration and segregation, and the role of future modes (e.g. personal aviation).- Multimodal, integrated ticketing and payment systems (i.e. Mobility as a Service).- Constraints and pricing on vehicle use either applied zonally, by mode, or other means.- Policy measures targeted at specific populations.The second underpinning theme of the PhD will be a set of evaluation measures that capture the implications of AVs on urban systems and society. During this stage it will be important to consider the wide-reaching effects of autonomous mobility on established social systems. Again, we are interested in both conventional and radical perspectives on these implications. In relation to the varying system configurations described above, these implications might include:- Changes in spatial flows, traffic density, and demand for parking.- Changes in service performance and travel times, differentiated by population characteristics (e.g. by demographic group, deprived populations).- Displacement of vehicle emissions and environmental burdens.- Changes in accessibility to different locations, services, and opportunities (e.g. health, education, commerce) brought on by mobility system changes.- Changes in the experienced city, including the impact on community cohesion, tranquillity, happiness, and so on.These models of mobility will be constructed using agent-based modelling, which will enable the exploration of scenarios at fine spatial and population scales. Within an ABM in place, in partnership with stakeholder, we will explore policy and urban design solutions aimed at maximising the benefits of autonomous mobility for the city and its citizens. By building ABMs of mobility at the urban scale, innovative solutions towards the inherent computational challenges can also be expected to be an output of the research. The PhD project will interface with and benefit from the vast array of research into agent-based modelling, urban analytics, and future mobility ongoing in the School of Geography, Institute for Transport Studies, and Leeds Institute for Data Analytics (LIDA).