不利条件下的场景适应：用于路边交通感知的多传感器融合框架

IF 2.8 3区工程技术 Q3 TRANSPORTATION

Journal of Intelligent Transportation Systems Pub Date : 2024-08-19 DOI:10.1080/15472450.2024.2390844

Kong Li, Zhe Dai, Chen Zuo, Xuan Wang, Hua Cui, Huansheng Song, Mengying Cui

引用次数: 0

摘要

强大的路边交通感知需要在各种不利条件下整合多源传感器的优势，这虽然具有挑战性，但对于制定有效的交通管理方案却不可或缺。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Scene adaptation in adverse conditions: a multi-sensor fusion framework for roadside traffic perception

Robust roadside traffic perception requires integrating the strengths of multi-source sensors under various adverse conditions, which is challenging but indispensable for formulating effective traf...

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来源期刊

Journal of Intelligent Transportation Systems 工程技术-运输科技

CiteScore

8.80

自引率

19.40%

发文量

审稿时长

15 months

期刊介绍： The Journal of Intelligent Transportation Systems is devoted to scholarly research on the development, planning, management, operation and evaluation of intelligent transportation systems. Intelligent transportation systems are innovative solutions that address contemporary transportation problems. They are characterized by information, dynamic feedback and automation that allow people and goods to move efficiently. They encompass the full scope of information technologies used in transportation, including control, computation and communication, as well as the algorithms, databases, models and human interfaces. The emergence of these technologies as a new pathway for transportation is relatively new. The Journal of Intelligent Transportation Systems is especially interested in research that leads to improved planning and operation of the transportation system through the application of new technologies. The journal is particularly interested in research that adds to the scientific understanding of the impacts that intelligent transportation systems can have on accessibility, congestion, pollution, safety, security, noise, and energy and resource consumption. The journal is inter-disciplinary, and accepts work from fields of engineering, economics, planning, policy, business and management, as well as any other disciplines that contribute to the scientific understanding of intelligent transportation systems. The journal is also multi-modal, and accepts work on intelligent transportation for all forms of ground, air and water transportation. Example topics include the role of information systems in transportation, traffic flow and control, vehicle control, routing and scheduling, traveler response to dynamic information, planning for ITS innovations, evaluations of ITS field operational tests, ITS deployment experiences, automated highway systems, vehicle control systems, diffusion of ITS, and tools/software for analysis of ITS.