  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".
