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The impact of Automated Vehicles (AVs) on urban geography has been widely speculated, though there is little quantitative evidence in the literature to establish the magnitude of such effects. To quantify the impact of the greater precision of automated driving on the spatial efficiency of off-street parking facilities, we develop a mixed integer nonlinear model (solved via a branch-and-cut approach) and present comparisons against industry-standard requirements for human-driving operation. We demonstrate that gains on the order of 40-50% in spatial efficiency (parking spaces per unit area) are in principle achievable while ensuring that each parked vehicle is independently accessible. We further show that the large majority of these efficiency gains can be obtained under current automotive engineering practice in which only the front two wheels pivot. There is a need for standardized methods that take the parking supply of a city as an input and calculate both the aggregate (citywide) efficiency impacts of automated driving and the spatial distribution of the effects. This study is intended as an initial step towards this objective., 1. Introduction Automation technologies for automobiles and other road vehicles are becoming increasingly available commercially, with further advances anticipated in coming years in both fundamental technology and its manifestation as [...]

This study is the first to quantify throughput (saturation flow) of noncooperative automated vehicles when performing turning maneuvers, which are critical bottlenecks in arterial road networks. We first develop a constrained optimization problem based on AVs' kinematic behavior during a protected signal phase which considers both ABS-enabled and wheels-locked braking, as well as avoiding encroaching into oncoming traffic or past the edge-of-receiving-lane. We analyze noncooperative ('defensive') behavior, in keeping with the Assured Clear Distance Ahead legal standard to which human drivers are held and AVs will likely also be for the foreseeable future. We demonstrate that, under plausible behavioral parameters, AVs appear likely to have positive impacts on throughput of turning traffic streams at intersections, in the range of +0.2% (under the most conservative circumstances) to +43% for a typical turning maneuver. We demonstrate that the primary mechanism of impact of turning radius is its effect on speed, which is likely to be constrained by passenger comfort. We show heterogeneous per-lane throughput in the case of 'double turn lanes.' Finally, we demonstrate limited sensitivity to crash-risk criterion, with a 4% difference arising from a change from 1 in 10,000 to 1 in 100,000,000. The paper concludes with a brief discussion of policy implications and future research needs., 1. Introduction Within the functional lifetime of much of today's road infrastructure, vehicle automation is expected to impact a range of important aspects of the transportation system, including traffic operations [...]