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道路交通安全研究的现状与热点分析

万明 吴倩 严利鑫 万平

万明, 吴倩, 严利鑫, 万平. 道路交通安全研究的现状与热点分析[J]. 交通信息与安全, 2022, 40(2): 11-21. doi: 10.3963/j.jssn.1674-4861.2022.02.002
引用本文: 万明, 吴倩, 严利鑫, 万平. 道路交通安全研究的现状与热点分析[J]. 交通信息与安全, 2022, 40(2): 11-21. doi: 10.3963/j.jssn.1674-4861.2022.02.002
WAN Ming, WU Qian, YAN Lixin, WAN Ping. A Review of Current Situation and Hot Spots of Road Safety Research[J]. Journal of Transport Information and Safety, 2022, 40(2): 11-21. doi: 10.3963/j.jssn.1674-4861.2022.02.002
Citation: WAN Ming, WU Qian, YAN Lixin, WAN Ping. A Review of Current Situation and Hot Spots of Road Safety Research[J]. Journal of Transport Information and Safety, 2022, 40(2): 11-21. doi: 10.3963/j.jssn.1674-4861.2022.02.002

道路交通安全研究的现状与热点分析

doi: 10.3963/j.jssn.1674-4861.2022.02.002
基金项目: 

国家自然科学基金项目 52162049

国家自然科学基金项目 52062014

江西省科技厅03专项及5G项目 20212ABC03A07

江西省自然科学基金项目 20202BABL212009

江西省自然科学基金项目 20212BAB202010

江西省高校人文社会科学研究项目 GL19204

详细信息
    作者简介:

    万明(1961—),硕士,教授.研究方向:道路交通安全、交通管理与设计.E-mail: wanming@ecjtu.edu.cn

    通讯作者:

    严利鑫(1988—),博士,副教授.研究方向:智能网联汽车关键技术、交通安全及事故致因分析、驾驶行为机理. E-mail: yanlixinits@163.com

  • 中图分类号: U491.3

A Review of Current Situation and Hot Spots of Road Safety Research

  • 摘要: 道路交通事故的产生对民众的生命安全和财产损失影响巨大,国内外学者在该方面进行了大量的研究。为了整体把握道路交通事故研究热点及发展趋势,从中国知网(CNKI)核心期刊数据库和Web of Science核心合集数据库选取了2000—2020年与道路交通事故相关的3 943篇文献为数据源,借助CiteSpace和VOSviewer文献计量软件平台从文献分布特征、关键词共现、关键词聚类、关键词突现等方面进行分析,并在此基础上从事故黑点鉴别与影响因素分析、事故安全评价与事故预测、事故伤害(RTI)的流行病学研究和预防、事故处理与安全管理、事故仿真与驾驶行为分析这5个研究方向分析道路交通安全的研究趋势与热点问题。研究表明:①从作者合作方面分析发现道路交通事故研究具有多学科交叉性质;②对关键词共现分析发现国内外期刊关键词共现类别基本一致,说明国内外对道路交通事故方面的研究具有较强的一致性;③数据分析发现当前研究还存在实时交通事故评价手段欠缺、道路交通伤害数据结构不统一、事故仿真模型的通用性与有效性有待于进一步提高等问题;④从研究趋势的演进来看,未来的研究趋势主要集中在道路交通事故侵权责任研究、道路交通事故对道路通行能力的影响等方面。

     

  • 图  1  2000—2020年道路交通事故研究载文量分布图

    Figure  1.  Distribution of research papers on road safety from 2000 to 2020

    图  2  CNKI主要研究群体共现图谱

    Figure  2.  CNKI cooccurrence map of main research groups

    图  3  Web of Science主要研究群体共现图谱

    Figure  3.  Web of Science cooccurrence map of main research groups

    图  4  CNKI关键词共现知识图谱

    Figure  4.  CNKI keywords co-occurrence knowledge map

    图  5  Web of Science关键词共现知识图谱

    Figure  5.  Web of Science keywords co-occurrence knowledge map

    图  6  CNKI关键词共现网络聚类图谱

    Figure  6.  CNKI keyword co-occurrence network cluster map

    图  7  Web of Science关键词共现网络聚类图谱

    Figure  7.  Web of Science keyword co-occurrence network

    图  8  CNKI关键词聚类图

    Figure  8.  CNKI keyword cluster diagram

    图  9  Web of science关键词聚类图

    Figure  9.  Web of science keyword cluster diagram

    图  10  道路交通事故研究关键词突现检测图

    Figure  10.  Road safety research keyword burst detection chart

    表  1  CNKI从事道路交通事故研究的代表性学者

    Table  1.   CNKI representative scholars engaged in road safety research

    序号 中心性 作者 序号 被引频次 作者
    1 15 周继红 1 19 王正国
    2 14 王正国 2 9 周继红
    3 10 李桢 3 8 刘锐
    4 9 邱俊 4 7 付锐
    5 9 李立 5 7 尹志勇
    6 9 段腾龙 6 7 刘小明
    7 9 张良 7 6 高建刚
    8 9 蒋志全 8 5 赵玲
    9 9 何永旺 9 5 邵春福
    10 2 代维 10 5 刘浩学
    下载: 导出CSV

    表  2  Web of Science从事道路交通事故研究的代表性学者

    Table  2.   Web of Science representative scholars engaged in road safety research

    序号 中心性 作者 序号 被引频次 作者
    1 7 Laumon Bernard 1 6 Park Kee B
    2 6 Negishi Kazuno 2 5 Laumon Bernard
    3 6 Yamagata Bun 3 5 Hitosugi Masahito
    4 6 Yamamoto Yasuharu 4 5 Morland Jorg
    5 6 Lauwaert Door 5 4 Charnay Pierrette
    6 6 Hotta Ryo 6 4 Hours Martine
    7 6 Tsutsumimoto Kota 7 4 Rehman Lal
    8 6 Deynse Helena Van 8 4 Xing Yingying
    9 6 Makizako Hyuma 9 4 Pereznuez Ricardo
    10 6 Belleghem Griet Van 10 4 Lu Jian
    下载: 导出CSV

    表  3  CNKI期刊载文量分布

    Table  3.   CNKI distribution of journal articles  单位: 篇

    期刊 数据库 2000—2005年 2006—2010年 2011—2015年 2016—2020年 合计
    《公路》 北大核心 14 25 31 12 82
    《公路交通科技》 CSCD 28 14 12 4 58
    《中国安全科学学报》 CSCD 0 27 18 13 58
    《中华创伤杂志》 CSCD 17 12 10 4 43
    《中国公路学报》 EI 8 2 5 15 30
    《中国法医学杂志》 CSCD 0 6 12 10 28
    《长安大学学报(自然科学版)》 CSCD 9 9 2 6 26
    《交通运输工程学报》 EI 1 17 6 1 25
    《保险研究》 CSSCI 1 7 11 5 24
    《重庆交通大学学报(自然科学版)》 CSCD 0 8 9 7 24
    《中国安全生产科学技术》 CSCD 0 5 5 10 20
    《中外公路》 北大核心 2 9 8 1 20
    合计 80 141 129 88 438
    下载: 导出CSV

    表  4  Web of Science期刊共被引分析

    Table  4.   Web of Science analysis of journal co-citation

    序号 被引频次 期刊 序号 中心性 期刊
    1 924 Accident Analysis & Prevention 1 11 Acta Otorhinolaryngologica
    2 526 Journal of Orthopaedic Trauma 2 10 American Journal of Psychiatry
    3 396 International Journal of the Care of Injured 3 10 Journal of Neurotrauma
    4 365 The Lancet 4 9 Addiction
    5 363 Traffic Injury Prevention 5 8 BMCPublicHealth
    6 283 Injury Prevention 6 8 Journal of Bone and Joint Surgery-American Volume
    7 281 Journal of Safety Research 7 8 Spine
    8 256 Transportation Research Record 8 8 Sleep
    9 246 British Medical Joural 9 8 Journal of Oral and Maxillofacial Surgery Medicine and Pathology
    10 222 Jama-journal of the American Medical Association 10 7 Journal of Cranio-maxillofacial Surgery
    下载: 导出CSV

    表  5  CNKI与Web of Science关键词共现中心性表

    Table  5.   CNKI and Web of Science keywords co-occurrence frequency and centrality table

    序号 CNKI 序号 Web of science
    关键词 中心性 关键词 中心性
    1 道路交通事故 41 1 risk factor 9
    2 交通安全 27 2 safety 9
    3 交通工程 27 3 motor vehicle accident 9
    4 高速公路 23 4 crash 8
    5 影响因素 12 5 pattern 6
    6 交强险 10 6 fracture 5
    7 安全评价 9 7 driver 5
    8 自动驾驶汽车 8 8 trend 48
    9 运行速度 8 9 management 38
    10 交通安全法 7 10 impact factor 27
    下载: 导出CSV
  • [1] HE Y, YANG S, CHAN C Y, et al. Visualization analysis of intelligent vehicles research field based on mapping knowledge domain[J]. IEEE Transactions on Intelligent Transportation Systems, 2020, 22(9): 5721-5736.
    [2] ZOU X, YUE W L, VU H L. Visualization and analysis of mapping knowledge domain of road safety studies[J]. Accident Analysis & Prevention, 2018, 118(6): 131-145.
    [3] 李杰, 曾叙砜, 李平, 等. 道路交通安全文献的知识可视化综述[J]. 交通信息与安全, 2020, 38(1): 13-19+26. doi: 10.3963/j.jssn.1674-4861.2020.01.002

    LI J, ZENG X F, LI P, et al. Visualization review of road traffic safety literature[J]. Journal of Transport Information and Safety, 2021, 38(1): 13-19+26. (in Chinese) doi: 10.3963/j.jssn.1674-4861.2020.01.002
    [4] 段腾龙, 何永旺, 李桢, 等. 基于PC-Crash软件的人-车碰撞道路交通事故重建[J]. 法医学杂志, 2019, 35(4): 440-443. https://www.cnki.com.cn/Article/CJFDTOTAL-FYXZ201904013.htm

    DUAN T L, HE Y W, LI Z, et al. Reconstruction of vehicle-pedestrian collision road traffic accidents based on PC-Crash software[J]. Journal of Forensic Medicine, 2019, 39 (4): 440-443. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-FYXZ201904013.htm
    [5] 张良, 周继红, 邱俊, 等. 2000—2006年重庆地区老年人道路交通伤害特点[J]. 重庆医学, 2011, 40(15): 1457-1459. doi: 10.3969/j.issn.1671-8348.2011.15.001

    ZHANG L, ZHOU J H, QIU J, et al. Characteristics of traffic injuries among elderly people in Chongqing between 2000 and 2006[J]. Chongqing Medicine, 2011, 40(15): 1457-1459. (in Chinese) doi: 10.3969/j.issn.1671-8348.2011.15.001
    [6] 刘小明, 李颖宏, 陈昱靦, 等. 基于改进BML模型的交通事故下路网交通运行状态分析[J]. 交通运输系统工程与信息, 2010, 10(2): 122-129. doi: 10.3969/j.issn.1009-6744.2010.02.020

    LIU X M, LI Y H, CHEN Y S, et al. Road net traffic status analysis under traffic accident based on improved BML model[J]. Journal of Transportation Systems Engineering and Information Technology, 2010, 10(2): 122-129. (in Chinese) doi: 10.3969/j.issn.1009-6744.2010.02.020
    [7] 高建刚, 陈宏云, 许诺, 等. 国外乡村公路交通安全保障措施介绍[J]. 公路交通科技, 2010, 27(8): 120-126+142. doi: 10.3969/j.issn.1002-0268.2010.08.023

    GAO J G, CHEN H Y, XU N, et al. Road safety guarantee measures of foreign rural roads[J]. Journal of Highway and Transportation Research and Development, 2010, 27(8): 120-126+142. (in Chinese) doi: 10.3969/j.issn.1002-0268.2010.08.023
    [8] 赵玲, 许宏科, 程鸿亮. 基于最优加权组合模型的道路交通事故预测[J]. 计算机工程与应用, 2013, 49(24): 11-15. doi: 10.3778/j.issn.1002-8331.1305-0324

    ZHAO L, XU H K, CHENG H L. Road traffic accidents prediction based on optimal weighted combined model[J]. Computer Engineering and Applications, 2013, 49(24): 11-15. (in Chinese) doi: 10.3778/j.issn.1002-8331.1305-0324
    [9] YAMAMOTO Y, HIRANO J, YOSHITAKE H, et al. Machine-learning approach to predict on-road driving ability in healthy older people[J]. Psychiatry and Clinical Neurosciences, 2020, 74(9): 488-495. doi: 10.1111/pcn.13084
    [10] HOTTA R, MAKIZAKO H, DOIT, et al. Cognitive function and unsafe driving acts during an on-road test among community-dwelling older adults with cognitive impairments[J]. Geriatrics & Gerontology International, 2018, 18(6): 847-852.
    [11] HOURS M, KHATI I, CHARNAY P, et al. One year after mild injury: Comparison of health status and quality of life between patients with whiplash versus other injuries[J]. The Journal of Rheumatology, 2014, 41(3): 528-538. doi: 10.3899/jrheum.130406
    [12] XING Y, CHEN S, ZHU S, et al. Exploring risk factors contributing to the severity of hazardous material transportation accidents in China[J]. International Journal of Environmental Research and Public Health, 2020, 17(4): 1344-1363. doi: 10.3390/ijerph17041344
    [13] ZHOU X, ZHAO G. Global liposome research in the period of 1995—2014: A bibliometric analysis[J]. Scientometrics, 2015, 105(1): 231-248. doi: 10.1007/s11192-015-1659-6
    [14] ZHANG X D, WANG C X, JIANG H H, et al. Trends in research related to high myopia from 2010 to 2019: A bibliometric and knowledge mapping analysis[J]. International Journal of Ophthalmology, 2021, 14(4): 589-599. doi: 10.18240/ijo.2021.04.17
    [15] BORSOS A, CAFISO S, D'AGOSTINO C, et al. Comparison of Italian and Hungarian black spot ranking[J]. Transportation Research Procedia, 2016, 14(5): 2148-2157.
    [16] 耿超, 彭余华. 基于动态分段和DBSCAN算法的交通事故黑点路段鉴别方法[J]. 长安大学学报(自然科学版), 2018, 38(5): 131-138. doi: 10.3969/j.issn.1671-8879.2018.05.016

    GENG C, PENG Y H. Identification method of traffic accident black spots based on dynamic segmentation and DBSCAN algorithm[J]. Journal of Chang'an University(Natural Science Edition), 2018, 38(5): 131-138. (in Chinese) doi: 10.3969/j.issn.1671-8879.2018.05.016
    [17] 刘志强, 王玲, 张爱红, 等. 基于贝叶斯模型的雾霾天高速公路交通事故发生机理研究[J]. 重庆理工大学学报(自然科学), 2018, 32(1): 43-49. https://www.cnki.com.cn/Article/CJFDTOTAL-CGGL201801007.htm

    LIU Z Q, WANG L, ZHANG A H, et al. Study on traffic accidents occurrence mechanism in haze weather on the highway[J]. Journal of Chongqing University of Technology (Natural Science), 2018, 32(1): 43-49. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-CGGL201801007.htm
    [18] 赵丹, 马社强, 张雨萌, 等. 农村公路交叉口交通事故特征关联性与风险因素分析[J]. 中国安全科学学报, 2020, 30 (7): 146-151. https://www.cnki.com.cn/Article/CJFDTOTAL-ZAQK202007023.htm

    ZHAO D, MA S Q, ZHANG Y M, et al. Correlation and risk factors analysis of traffic crash at intersections on rural highways[J]. China Safety Science Journal, 2020, 30(7): 146-151. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-ZAQK202007023.htm
    [19] TANG J, LIANG J, HAN C, et al. Crash injury severity analysis using a two-layer Stacking framework[J]. Accident Analysis & Prevention, 2019, 122(10): 226-238.
    [20] WANG C, XU C, XIA J, et al. A combined use of microscopic traffic simulation and extreme value methods for traffic safety evaluation[J]. Transportation Research Part C: Emerging Technologies, 2018, 90(3): 281-291.
    [21] 梁心雨, 郭彤, 孟祥海. 基于三角模糊数权重算法的宏观交通安全评价方法[J]. 交通信息与安全, 2017, 35(4): 20-28+35. doi: 10.3963/j.issn.1674-4861.2017.04.003

    LIANG X Y, GUO T, MENG X H. A method on macroscopic traffic safety evaluation based on weighting triangular fuzzy number algorithm[J]. Journal of Transport Information and Safety, 2017, 35(4): 20-28+35. (in Chinese) doi: 10.3963/j.issn.1674-4861.2017.04.003
    [22] TIAN Z, ZHANG S. Application of multi-attribute group decision-making methods in urban road traffic safety evaluation with interval-valued intuitionistic fuzzy information[J]. Journal of Intelligent & Fuzzy Systems, 2021, 40(3): 5337-5346.
    [23] USMAN M, CARIE A, MARAPELLI B, et al. A human-in-the-loop probabilistic CNN-Fuzzy Logic framework for accident prediction in vehicular networks[J]. IEEE Sensors Journal, 2021, 21(14): 15496-15503. doi: 10.1109/JSEN.2020.3023661
    [24] TANG J, ZHENG L, HAN C, et al. Statistical and machine-learning methods for clearance time prediction of road incidents: a methodology review[J]. Analytic Methods in Accident Research, 2020, 27(2): 100123-100138.
    [25] 戢小辉. 基于灰色关联的LS-SVM道路交通事故预测[J]. 计算机应用研究, 2016, 33(3): 806-809. doi: 10.3969/j.issn.1001-3695.2016.03.037

    JI X H. Forecast model of road traffic accidents based on LS-SVM with grey correlation analysis[J]. Application Research of Computers, 2016, 33(3): 806-809. (in Chinese) doi: 10.3969/j.issn.1001-3695.2016.03.037
    [26] 高珍, 高屹, 余荣杰, 等. 连续数据环境下的道路交通事故风险预测模型[J]. 中国公路学报, 2018, 31(4): 280-287. doi: 10.3969/j.issn.1001-7372.2018.04.032

    GAO Z, GAO Y, YU R J, et al. Road crash risk prediction model for continuous streaming data environment[J]. China Journal of Highway and Transport, 2018, 31(4): 280-287. (in Chinese) doi: 10.3969/j.issn.1001-7372.2018.04.032
    [27] 黄合来, 罗启章, 彭韵颖, 等. 山区高速公路隧道群路段危化品运输风险评价体系研究[J]. 中南大学学报(自然科学版), 2018, 49(8): 2107-2114. https://www.cnki.com.cn/Article/CJFDTOTAL-ZNGD201808034.htm

    HUANG H L, LUO Q Z, PENG Y Y, et al. Risk evaluation for hazardous chemicals transportation at mountainous freeway with tunnels groups[J]. Journal of Central South University(Science and Technology), 2018, 49(8): 2107-2114. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-ZNGD201808034.htm
    [28] 梁明明, 张允, 汪媛, 等. 气象因素与交通事故伤害关联性的系统评价[J]. 中华疾病控制杂志, 2020, 24(2): 222-227. https://www.cnki.com.cn/Article/CJFDTOTAL-JBKZ202002020.htm

    LIANG M M, ZHANG Y, WANG Y, et al. A systematic review on the association between meteorological factors with traffic accident injury[J]. Chinese Journal of Disease Control & Prevention, 2020, 24(2): 222-227. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JBKZ202002020.htm
    [29] 杨嘉璐, 钟艺琪, 梅海卿, 等. 共享单车道路交通伤害的流行特征及危险因素研究[J]. 中华疾病控制杂志, 2018, 22 (10): 1012-1015. https://www.cnki.com.cn/Article/CJFDTOTAL-JBKZ201810011.htm

    YANG J L, ZHONG Y Q, MEI H Q, et al. Study on epidemic characteristics and risk factors of road traffic injury on shared bicycles[J]. Chinese Journal of Disease Control & Prevention, 2018, 22(10): 1012-1015. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JBKZ201810011.htm
    [30] WU Y, LIU C, LAN S, et al. Real-time 3D road scene based on virtual-real fusion method[J]. IEEE Sensors Journal, 2015, 15(2): 750-756. doi: 10.1109/JSEN.2014.2354331
    [31] 程啸. 民法典侵权责任编中机动车交通事故责任的完善[J]. 法学杂志, 2019, 40(1): 64-74.

    CHENG X. Advices on improving regulations of auto liability in the tort law of China civil code[J]. Law Science Magazine, 2019, 40(1): 64-74. (in Chinese)
    [32] 马宁. 中国交强险立法的完善: 保险模式选择与规范调适[J]. 收藏, 2019, 13(5): 149-167. https://www.cnki.com.cn/Article/CJFDTOTAL-QHFX201905009.htm

    MA N. The improvement of China's compulsory traffic accident liability insurance: Selection of insurance model and regulatory adjustment[J]. Tsinghua University Law Journal, 2019, 13(5): 149-167. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-QHFX201905009.htm
    [33] 庞明宝, 蔡章辉. 一个山区高速公路下纵坡弯道可能事故的CAM[J]. 系统仿真学报, 2018, 30(4): 1414-1422. https://www.cnki.com.cn/Article/CJFDTOTAL-XTFZ201804026.htm

    PANG M B, CAI Z H. CAM of possible accident for longitudinal slope curve of mountain freeway[J]. Journal of System Simulation, 2018, 30(4): 1414-1422. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-XTFZ201804026.htm
    [34] 李静, 王占永, 蔡铭. 信号交叉口左转待行区综合效益评估[J]. 中山大学学报(自然科学版), 2019, 58(3): 110-117. https://www.cnki.com.cn/Article/CJFDTOTAL-ZSDZ201903014.htm

    LI J, WANG Z Y, CAI M. Comprehensive benefit evaluation of the left-turn waiting zone on signalized intersection[J]. Acta Scientiarum Naturalium Universitatis Sunyatseni, 2019, 58 (3): 110-117. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-ZSDZ201903014.htm
    [35] 龚鹏飞, 常正辉, 徐雨. 城市道路应急交通组织措施及仿真评价[J]. 中国安全生产科学技术, 2020, 16(10): 139-145. https://www.cnki.com.cn/Article/CJFDTOTAL-LDBK202010028.htm

    GONG P F, CHANG Z H, XU Y. Emergency traffic organization measures and simulated evaluation of urban roads[J]. Journal of Safety Science and Technology, 2020, 16(10): 139-145. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-LDBK202010028.htm
    [36] 范双双, 张梦洁, 漆书林. 驾驶员异常驾驶行为与人格类型调查研究[J]. 交通信息与安全, 2018, 36(3): 99-104. doi: 10.3963/j.issn.1674-4861.2018.03.014

    FAN S S, ZHANG M J, QI S L. The relationship between abnormal driving behaviors and personality types of drivers[J]. Journal of Transport Information and Safety, 2018, 36(3): 99-104. (in Chinese) doi: 10.3963/j.issn.1674-4861.2018.03.014
    [37] ZAHID M, CHEN Y Z, KHAN S, et al. Predicting risky and aggressive driving behavior among taxi drivers: do spatio-temporal attributes matter?[J]. International Journal of Environmental Research and Public Health, 2020, 17(11): 3937-3958. doi: 10.3390/ijerph17113937
    [38] 蔡晓禹, 雷财林, 彭博, 等. 基于驾驶行为和信息熵的道路交通安全风险预估[J]. 中国公路学报, 2020, 33(6): 190-201. doi: 10.3969/j.issn.1001-7372.2020.06.018

    CAI X Y, LEI C L, PENG B, et al. Road traffic safety risk estimation based on driving behavior and information entropy[J]. China Journal of Highway and Transport, 2020, 33 (6): 190-201. (in Chinese) doi: 10.3969/j.issn.1001-7372.2020.06.018
    [39] HU J, ZHANG X, MAYBANK S. Abnormal driving detection with normalized driving behavior data: A deep learning approach[J]. IEEE Transactions on Vehicular Technology, 2020, 69(7): 6943-6951. doi: 10.1109/TVT.2020.2993247
    [40] 林垚, 张丽, 张晗. 基于Cite Space的我国路面工程领域发展状况分析[J]. 交通运输研究, 2021, 7(1): 104-114. https://www.cnki.com.cn/Article/CJFDTOTAL-JTBH202101013.htm

    LIN Y, ZHANG L, ZHANG H. Domestic development status of pavement engineering based on CiteSpace[J]. Transport Research, 2021, 7(1): 104-114. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JTBH202101013.htm
    [41] 杨昆鹏. 无人驾驶汽车碰撞程序的刑法正当性——基于行为功利主义理论[J]. 新疆大学学报(哲学·人文社会科学版), 2021, 49(5): 19-27. https://www.cnki.com.cn/Article/CJFDTOTAL-XJDB202105003.htm

    YANG K P. Legitimacy of the criminal law on the procedure of driverless car crashes-based on the theory of act utilitarianism[J]. Journal of Xinjiang University(Philosophy, Humanities & Social Sciences), 2021, 49(5): 19-27. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-XJDB202105003.htm
    [42] KUANG L, YAN H, ZHU Y, et al. Predicting duration of traffic accidents based on cost-sensitive Bayesian network and weighted K-nearest neighbor[J]. Journal of Intelligent Transportation Systems, 2019, 23(2): 161-174. doi: 10.1080/15472450.2018.1536978
    [43] JIA W, PENG H, RUAN N, et al. WiFind: driver fatigue detection with fine-grained Wi-Fi signal features[J]. IEEE Transactions on Big Data, 2020, 6(2): 269-282. doi: 10.1109/TBDATA.2018.2848969
    [44] CHANG H, PARK D. Potentialities of vehicle trajectory big data for monitoring potentially fatigued drivers and explaining vehicle crashes on motorway sections[J]. Sustainability, 2020, 12(15): 5877-5893. doi: 10.3390/su12155877
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  • 收稿日期:  2021-06-22
  • 网络出版日期:  2022-05-18

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