| 20 | 0 | 20 |
| 下载次数 | 被引频次 | 阅读次数 |
山区道路路况差、行车环境复杂，交通事故频发且伤亡严重。为提高山区道路行车安全水平，以2019—2023年桂林市山区道路交通事故数据为基础，采用考虑事故严重度的核密度估计方法综合评估交通事故高风险路段。首先，依据风险路段鉴别结果，将事故样本分为高、低风险两组；其次，通过分析事故风险关键影响因素，并依托贝叶斯网络构建山区道路交通事故高风险点预判模型。结果显示：道路类型、路口路段类型和中央隔离设施对事故伤亡程度具有显著影响，其中道路类型和中央隔离设施直接影响事故风险概率；构建的预判模型可评估不同事故形态、不同严重度下的事故风险概率。研究成果可为制定山区道路差异化事故预防政策提供决策依据。
Abstract：Mountainous road conditions are poor and driving environments are complex,leading to frequent traffic accidents with severe casualties. To enhance the safety level of driving on mountainous roads,this study comprehensively assesses high-risk sections of traffic accidents based on the traffic accident data of mountainous roads in Guilin City from 2019 to 2023,using a kernel density estimation method that considers the severity of accidents. Firstly,the accident samples are divided into high-risk and low-risk groups based on the identification results of risk sections. Secondly,chi-square analysis is used to explore the key influencing factors of accident risk,and a Bayesian network is employed to construct a prediction model for high-risk points of traffic accidents on mountainous roads. The results show that road type,intersection and section type,and central isolation facilities have a significant impact on the severity of accidents,among which road type and central isolation facilities directly affect the probability of accident risk. The constructed prediction model can assess the probability of accident risk under different accident forms and severity levels. The research results can provide a decision-making basis for formulating differentiated accident prevention policies for mountainous roads.
[1]戢晓峰，耿昭师，普永明，等.接入道路对山区双车道公路穿村镇路段事故风险影响[J].中国安全科学学报，2022,32(5):155-162.JI X F,GENG Z S,PU Y M,et al.Influence of access roads on accident risks of mountainous two-lane highway passing through villages and towns segments[J].China Safety Science Journal,2022,32(5):155-162.
[2]刘尧，王颖志，王立君，等.交通事故的时空热点分析[J].浙江大学学报(理学版),2020,47(1):52-59.LIU Y,WANG Y Z,WANG L J,et al.Spatial-temporal hotspots analysis on traffic accidents[J].Journal of Zhejiang University (Science Edition),2020,47(1):52-59.
[3]ALI S S,AHMED M,MUMTAZ R,et al.Spatiotemporal clustering and analysis of road accident hotspots by exploiting GIS technology and kernel density estimation[J].The Computer Journal,2022,65(2):155-176.
[4]ATUMO E A,FANG T,JIANG X G.Spatial statistics and random forest approaches for traffic crash hot spot identification and prediction[J].International Journal of Injury Control and Safety Promotion,2022,29(2):207-216.
[5]GREGORIADES A,MOUSKOS K C.Black spots identification through a Bayesian networks quantification of accident risk index[J].Transportation Research Part C:Emerging Technologies,2013,28:28-43.
[6]于翔海，白佃国，于光，等.基于XGBoost模型的城市道路实时交通事故风险预测研究[J].公路交通科技，2023,40(4):237-247.YU X H,BAI D G,YU G,et al.Study on predicting real-time traffic accident risk of urban road basedon XGBoost model[J].Journal of Highway and Transportation Research and Development,2023,40(4):237-247.
[7]LUO W H,CAI F T,WU C N,et al.Bayesian network-based knowledge graph inference for highway transportation safety risks[J].Advances in Civil Engineering,2021,2021:6624579.
[8]CAI Q,ABDEL-ATY M,YUAN J H,et al.Real-time crash prediction on expressways using deep generative models[J].Transportation Research Part C:Emerging Technologies,2020,117:102697.
[9]GE H M,DONG L,HUANG M Y,et al.Adaptive kernel density estimation for traffic accidents based on improved bandwidth research on black spot identification model[J].Electronics,2022,11(21):3604.
[10]陈金林.基于网络核密度估计城市路网事故黑点鉴别研究[D].南京：东南大学，2015.CHEN J L.Research on identifing hotspots in the urban road networks based on the network kernel density estimation method[D].Nanjing:Southeast University,2015.
[11]温惠英，吴亚平，漆巍巍.山区公路事故黑点鉴别及其成因分析模型[J].重庆交通大学学报(自然科学版),2016,35(4):137-140.WEN H Y,WU Y P,QI W W.Models of identification and formulation cause analysis on accident black spots of mountainous highway[J].Journal of Chongqing Jiaotong University (Natural Sciences),2016,35(4):137-140.
[12]TOLA A M,DEMISSIE T A,SAATHOFF F,et al.Severity,spatial pattern and statistical analysis of road traffic crash hot spots in Ethiopia[J].Applied Sciences,2021,11(19):8828.
[13]FEIZIZADEH B,OMARZADEH D,SHARIFI A,et al.A GIS-based spatiotemporal modelling of urban traffic accidents in Tabriz city during the COVID-19 pandemic[J].Sustainability,2022,14(12):7468.
基本信息:
DOI：10.13291/j.cnki.djdxac.2026.04.005
中图分类号:U491.31
引用信息:
[1]程瑞,秘运健,盘烨,等.基于改进核密度估计的山区道路事故高风险点预判研究[J].大连交通大学学报,2026,47(04):37-45.DOI:10.13291/j.cnki.djdxac.2026.04.005.
基金信息:
国家自然科学基金项目(52262047); 广西自然科学基金项目(2022GXNSFBA035640,2023GXNSFAA026359); 桂林市科学研究与技术开发计划项目(20230120-7)
2026-08-17
2026-08-17
2026-08-17