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.
翻译:使用路边基础设施传感器的基础设施强化环境观念可被视为一种有效的解决办法,至少对城市道路交叉点或通往AV的曲线路段等某些感兴趣的区域而言是如此。然而,这些车辆在采购、安装和维护方面需要花费大量费用。因此,这些传感器必须具有战略性和最佳性,以便在公路使用者的整体安全方面产生最大效益。在本文件中,我们提出一种新颖的方法,以取得对城市AV部署特别有吸引力的V2X(车到每件车)基础设施传感器的最佳位置,其中考虑到各种因素,包括成本、覆盖面和冗余。我们综合了光谱和线性优化文献方面的最新进展,以便为城市规划者、交通分析和AV部署操作者提供工具。我们通过在具有代表性的环境下的实验性评估,证明了我们的方法的好处和实用性。