A Virtual Method for Optimizing Deployment of Roadside Monitoring Lidars at As-built Intersections
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影响因子：8.5
DOI码：10.1109/TITS.2023.3286384
所属单位：汽车与交通工程学院
发表刊物：IEEE Transactions on Intelligent Transportation Systems
刊物所在地：USA
摘要：Roadside monitoring Lidars (RMLs) will be a crucial part of the future intelligent transportation system. Current approaches for optimizing RMLs’ placement at intersections work in hypothetical environments which do not well reflect real-world situations. This article proposes a new virtual method (VM) for optimizing the deployment of RMLs at as-built intersections. The proposed VM operates in a virtual environment where both static background and dynamic agents are modeled by dense point clouds. The agents are driven by real-world motion data. Using RMLs’ parameters as inputs, a coarse-to-fine subsampling approach is developed to generate laser scans in the virtual world. An objective function is then defined by comparing the agents’ points in the generated laser scan sequences against their original models. Bayesian optimization is applied to maximize the objective function by setting the RMLs’ positions and poses as decision variables. Besides, batch processing strategy and parallel computing are used to accelerate the optimization process. The effectiveness of the proposed VM is demonstrated in a case study. The VM shall help road administrators make decisions on RMLs’ deployment at as-built intersections
合写作者：Shuyi Wang,Yiik Diew Wong,Said Easa
第一作者：Yang Ma
论文类型：期刊论文
通讯作者：Yubing Zheng
学科门类：工学
文献类型：J
是否译文：否
发表时间：2023-06-27
收录刊物：SCI、EI
附件：