  Vehicles with driving automation are increasingly being developed for
deployment across the world. However, the onboard sensing and perception
capabilities of such automated or autonomous vehicles (AV) may not be
sufficient to ensure safety under all scenarios and contexts.
Infrastructure-augmented environment perception using roadside infrastructure
sensors can be considered as an effective solution, at least for selected
regions of interest such as urban road intersections or curved roads that
present occlusions to the AV. However, they incur significant costs for
procurement, installation and maintenance. Therefore these sensors must be
placed strategically and optimally to yield maximum benefits in terms of the
overall safety of road users. In this paper, we propose a novel methodology
towards obtaining an optimal placement of V2X (Vehicle-to-everything)
infrastructure sensors, which is particularly attractive to urban AV
deployments, with various considerations including costs, coverage and
redundancy. We combine the latest advances made in raycasting and linear
optimization literature to deliver a tool for urban city planners, traffic
analysis and AV deployment operators. Through experimental evaluation in
representative environments, we prove the benefits and practicality of our
approach.
