Volume 40 Issue 2
Apr.  2022
Turn off MathJax
Article Contents
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

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

doi: 10.3963/j.jssn.1674-4861.2022.02.002
  • Received Date: 2021-06-22
    Available Online: 2022-05-18
  • Due to its great impacts on people's life and property loss, road safety research has been gained more and more attention in China and abroad. Inorder to grasp state of the art and the practice of road safety research, 3 943 papers related to road accidents from 2000 to 2020 are selected from the core periodical database in China National Knowledge Infrastructure(CNKI)and the core collection database of Web of Science.These papers are analyzed based on their publication year, distribution of journals, research institutions, scholars, and keywords, by using the CiteSpace and VOSviewer software. The research trends and hotspots of road safety have been reviewed from the following five aspects: identification of black spots and analysis of influencing factors, safety evaluation and prediction, epidemiological study and prevention of road traffic injury(RTI), response to accidents and safety management, accident simulation and driving behavior analysis. The results show that: ①road safety research has multi-disciplinary nature from the perspective of co-authorship analysis. ② Co-occurrence analysis of keywords shows that the categories of co-occurrence keywords in domestic and foreign journals are basically similar, which indicates that studies on road safetycarried out in Chinaare consistent with those abroad. ③Data analysis shows that there are still issues within the current research, such as the lack of real-time road safety evaluation methods, inconsistent data structure for accident-related injury data, and the effectiveness and applicability of accident simulation model need to be further improved. ④In terms of the evolution of road safety research, future research could mainly focus on tort liability and the impactsof accidents on road capacity.

     

  • loading
  • [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
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(10)  / Tables(5)

    Article Metrics

    Article views (2543) PDF downloads(327) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return