论文标题
在能量和吞吐量限制下放置雷达的位置升高
Elevated LiDAR Placement under Energy and Throughput Capacity Constraints
论文作者
论文摘要
高架LIDAR（ELID）有可能加快自动驾驶汽车的部署（AV），因为ELID可以减少与AV相关的能源支出，并且还可以用于其他智能运输系统应用，例如Urban 3D映射。在本文中，我们解决了计划框架的需求，以便其运营商拥有一个有效的工具来确定需要哪些资源来达到所需的城市道路覆盖范围。为此，我们开发了一个混合成员非线性约束优化问题，目的是最大程度地提高道路的有效面积覆盖范围，同时满足能量和吞吐量的容量约束。由于问题的非线性性，我们利用粒子群优化（PSO）来解决问题。在证明其在为现实情况找到解决方案方面的有效性之后，我们执行灵敏度分析以测试模型的一般能力。
Elevated LiDAR (ELiD) has the potential to hasten the deployment of Autonomous Vehicles (AV), as ELiD can reduce energy expenditures associated with AVs, and can also be utilized for other intelligent Transportation Systems applications such as urban 3D mapping. In this paper, we address the need for a planning framework in order for ITS operators to have an effective tool for determining what resources are required to achieve a desired level of coverage of urban roadways. To this end, we develop a mixed-integer nonlinear constrained optimization problem, with the aim of maximizing effective area coverage of a roadway, while satisfying energy and throughput capacity constraints. Due to the non-linearity of the problem, we utilize Particle Swarm Optimization (PSO) to solve the problem. After demonstrating its effectiveness in finding a solution for a realistic scenario, we perform a sensitivity analysis to test the model's general ability.
