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城市的人类体验产生重大影响。自动驾驶汽车（AVs）——从私家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，但也引发了有关它们对城市领域的影响以及人车互动性质变化的问题。完全自主移动系统的实施进一步提出了与访问、设计和车辆所有权相关的政策挑战。该博士项目将采用基于代理的模型（ABM）来探索自动驾驶汽车在城市尺度上的空间、社会和政策影响，从而研究自动驾驶汽车的这些更广泛的影响。研究的第一阶段将是定义一组自动移动的场景。自动驾驶汽车的本质意味着，这些场景可能包括从传统视角到对城市交通的全新看法。该项目将探讨这些不同的规划和政策情景如何表现为城市的不同结果。场景空间可能包括以下内容，但将在第一年的学习中更正式地勾画出来：-车辆所有权模型（例如共享，个人）。-自主的多模式混合，包括对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）。-多式联运、综合票务及支付系统（即流动即服务）。-按区域、模式或其他方式对车辆使用施加限制和定价。-针对特定人群的政策措施。博士学位的第二个基本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，重要的是要考虑到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观点和激进观点都感兴趣。与上述不同的系统配置相关，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（例如按人口群体、贫困人口）区分的服务表现和旅行时间的变化。-消除车辆废气和环境负担。-流动系统变化带来的不同地点、服务和机会（如卫生、教育、商业）可达性的变化。-体验城市的变化，包括对社区凝聚力、安宁、幸福等的影响。这些移动模型将使用基于代理的建模来构建，这将使人们能够在精细的空间和人口尺度上探索场景。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，旨在最大限度地为城市和市民带来自主出行的好处。通过在城市尺度上建立移动的ABMs，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。该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（LIDA）正在进行的关于基于代理的建模、城市分析和未来交通的大量研究相结合，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).