Virtual-real-fusion simulation framework for evaluating and optimizing small-spatial-scale placement of cooperative roadside sensing units
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影响因子：9.6
DOI码：10.1111/mice.13167
所属单位：合肥工业大学
发表刊物：Computer-aided Civil and Infrastructure Engineering
刊物所在地：美国
项目来源：安徽省青年科学基金(2308085QE188)；中央科研业务费(JZ2023HGTA0191, JZ2022HGTA0338)；加拿大自然科学基金；
摘要：Roadside sensing units’ (RSUs) perception capability may be substantially impaired by occlusion issue even they work cooperatively. However, the joint influence of static and dynamic occlusions in real-life situations remains inadequately considered in optimizing RSUs’ placement. This study proposes a virtual-real-fusion simulation (VRFS) framework that combines traffic simulation and point clouds of real-world road environment to optimize RSUs’ deployment. Point clouds and triangular meshes are used to model static and dynamic obstacles, respectively. A structure-retained spherical projection method is developed to efficiently emulate RSUs’ data collection. Based on the developed VRFS, the probabilistic occupancy maps (POM) are created to represent traffic scenarios. The POM-based cross entropy (CE) is proposed as the surrogate metric for evaluating the detection performance of cooperative RSUs. The Bayesian optimizer is applied to optimize the RSUs’ placement parameters (decision variables) by minimizing CE. Test results show that it is viable to use the POM-based CE as a proxy for evaluating cooperative RSUs’ sensing performance. Considering the occlusion effect adds to the efficacy of POM-based CE as a surrogate metric. Compared with traffic volume, the adverse effect of the proportion of large vehicles on RSUs’ detection performance is more significant. There are no significant patterns regarding how the optimized RSU positions vary with traffic parameters. The comparisons with existing methods further verify the importance of considering both static and dynamic occlusions in optimizing RSUs’ placement. Besides, the proposed method can yield better optimization results more efficiently than existing approaches.
合写作者：Zheng, Yubing,Wang, Shuyi,Wong, Yiik Diew
第一作者：Ma, Yang
论文类型：期刊论文
通讯作者：Said Easa
学科门类：工学
文献类型：J
字数：14000
ISSN号：1467-8667
是否译文：否
发表时间：2024-02-06
收录刊物：SCI、EI
发布期刊链接：https://onlinelibrary.wiley.com/doi/10.1111/mice.13167
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