Autonomous Vehicles (AVs) can potentially improve urban living by reducing accidents, increasing transportation accessibility and equity, and decreasing emissions. Realizing these promises requires the innovations of AV driving behaviors, city plans and infrastructure, and traffic and transportation policies to join forces. However, the complex interdependencies among AV, city, and policy design issues can hinder their innovation. We argue the path towards better AV cities is not a process of matching city designs and policies with AVs' technological innovations, but a process of iterative prototyping of all three simultaneously: Innovations can happen step-wise as the knot of AV, city, and policy design loosens and tightens, unwinds and reties. In this paper, we ask: How can innovators innovate AVs, city environments, and policies simultaneously and productively toward better AV cities? The paper has two parts. First, we map out the interconnections among the many AV, city, and policy design decisions, based on a literature review spanning HCI/HRI, transportation science, urban studies, law and policy, operations research, economy, and philosophy. This map can help innovators identify design constraints and opportunities across the traditional AV/city/policy design disciplinary bounds. Second, we review the respective methods for AV, city, and policy design, and identify key barriers in combining them: (1) Organizational barriers to AV-city-policy design collaboration, (2) computational barriers to multi-granularity AV-city-policy simulation, and (3) different assumptions and goals in joint AV-city-policy optimization. We discuss two broad approaches that can potentially address these challenges, namely, "low-fidelity integrative City-AV-Policy Simulation (iCAPS)" and "participatory design optimization".

翻译：自动驾驶汽车（AV）有望通过减少事故、提升交通可及性与公平性、降低排放来改善城市生活。实现这些愿景需要自动驾驶行为、城市规划与基础设施、交通政策三方面的创新协同发力。然而，自动驾驶、城市与政策设计问题之间复杂的相互依赖关系可能阻碍其创新。我们认为，通向更优自动驾驶城市之路并非简单地将城市设计与政策适配于自动驾驶技术革新，而是一个三者同步迭代原型化的过程：随着自动驾驶、城市与政策设计之结的松紧、解系，创新可逐步实现。本文提出核心问题：创新者如何通过同步且高效的方式，对自动驾驶、城市环境与政策进行创新以构建更优的自动驾驶城市？论文分两部分展开。首先，基于涵盖人机交互/人机协作、交通科学、城市研究、法律政策、运筹学、经济学及哲学等领域的文献综述，梳理自动驾驶、城市与政策设计决策间的关联网络。该图谱可帮助创新者跨越传统自动驾驶/城市/政策设计的学科边界，识别设计约束与机遇。其次，分别评述自动驾驶、城市与政策设计的研究方法，并指出三者融合的关键障碍：（1）组织层面的协作壁垒，（2）多粒度自动驾驶-城市-政策仿真的计算壁垒，（3）联合优化中不同假设与目标的冲突。本文探讨了两类潜在应对方案，即"低保真度城市-自动驾驶-政策集成仿真（iCAPS）"与"参与式设计优化"。