| “自动+人工”混合驾驶环境下交通管理研究综述 |
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| 引用本文： | 裴玉龙, 迟佰强, 吕景亮, 岳志坤. “自动+人工”混合驾驶环境下交通管理研究综述[J]. 交通信息与安全, 2021, 39(5): 1-11. doi: 10.3963/j.jssn.1674-4861.2021.05.001 |
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| 作者姓名： | 裴玉龙 迟佰强 吕景亮 岳志坤 |
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| 作者单位： | 东北林业大学交通学院 哈尔滨 150040 |
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| 基金项目： | 国家自然科学基金项目71771047国家自然科学基金项目51638004 |
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| 摘 要： | 为了解混合驾驶环境下交通管理的研究现状和发展趋势，以“自动驾驶汽车”发展现状为基础，分析自动驾驶汽车在混合驾驶环境下存在的问题，基于Citespace文献计量工具，CNKI核心数据库近24年（1997—2020年）有关自动驾驶研究的文献为研究数据源，从发文年代、期刊来源、研究机构、关键词等进行文献计量和可视化分析，并生成各研究机构间的关系网络图谱及关键词共现网络图谱。结果表明：国内近5年自动驾驶发文量呈上升趋势；《中国公路学报》为发文量最高的期刊；自动驾驶汽车研究的方向主要包括：①目标检测及场景感知研究；②决策与控制；③交通事故责任划定研究。在未来混合驾驶环境下交通管理应结合车路协同、高精度地图技术，从标志标线设计、信号配时优化、路权归属、交通事故责任划定等方面进行研究，使道路运输更安全、高效、便捷。
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| 关 键 词： | 智能交通 交通管理 自动驾驶 路径规划 场景感知 责任认定 混合驾驶 |
| 收稿时间： | 2021-05-23 |
An Overview of Traffic Management in "Automatic+Manual" Driving Environment |
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| PEI Yulong, CHI Baiqiang, LYU Jingliang, YUE Zhikun. An Overview of Traffic Management in "Automatic+Manual" Driving Environment[J]. Journal of Transport Information and Safety, 2021, 39(5): 1-11. doi: 10.3963/j.jssn.1674-4861.2021.05.001 |
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| Authors: | PEI Yulong CHI Baiqiang LYU Jingliang YUE Zhikun |
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| Affiliation: | School of Traffic and Transportation, Northeast Forestry University, Harbin 150040, China |
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| Abstract: | Based on the development status of "automatic driving vehicle", the problems existing in mixed driving environment of autopilot cars are analyzed to understand the current situations and development trends of traffic management in the mixed driving environment. In terms of the Citespace bibliometric tool, the CNKI core database in the past 24 years(1997—2020)is taken as the data source. The bibliometric and visual analysis are performed from publication year, journal source, research institution, and keywords, and network maps of relationships between research institutions and keyword co-occurrence is generated. The results show that the number of automatic driving documents has been increasing in China in recent 5 years. The journal with the most of related papers is China Journal of Highway and Transport. Its research directions of the automatic driving vehicles include: ①Research on target detection and scene perception. ②Research on decision making and control. ③Research on responsibility delineation of traffic accidents. In the future, for mixed driving environment, traffic management should combine vehicle-road coordination and high-precision map technology, study from the design of signs and markings, signal timing optimization, ownership of road rights, and the delineation of traffic accident responsibilities, thus making road transportation safe, efficient and convenient. |
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| Keywords: | intelligent transportation system traffic management autonomous driving route planning scene awareness confirmation of responsibility hybrid driving |
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