基于多元统计方法的城市道路交通事故分析研究
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摘要
随着机动化水平的不断提高,城市道路交通安全形势日趋严峻。如何减少事故发生起数、减轻事故严重程度,已成为人们普遍关注的问题之一。结合道路交通事故随机事件的特点,利用多元统计方法分析事故及相关因素数据,可有效获取风险因素对事故影响的显著规律,从而提出有效改善措施。文中以城市道路交通事故为研究对象,结合城市道路上的突出交通安全问题,开展了事故发生频次、事故严重程度以及风险交通行为影响因素分析等方面的研究。
为了明确城市道路的突出交通安全问题,利用多项事故统计指标对城市道路交通事故在不同时间、不同道路类型、不同路口路段类型、不同车辆使用性质以及不同事故类型上的分布特征进行了描述性统计分析,发现主干路和次干路、四叉信号交叉口和无控制出入路段、出租和公交客运的交通安全问题,以及机动车与自行车碰撞事故值得关注。
在总结国内外道路交通事故分析研究的基础上,提出了城市道路交通事故分析概念模型,并结合上述交通安全突出问题,设计了城市道路交通事故分析体系,具体包括三个方面：城市干道网络中信号交叉口和无控制出入路段事故发生频次分析、城市道路机动车与自行车碰撞事故分析以及城市道路公共运输驾驶员“心理-行为-事故”影响链分析。
随机选取北京市城市干道网络中108个四叉信号交叉口和123.5 km无控制出入路段,收集了4年的轻伤及以上伤亡事故和相关交通因素信息,构建了纵向数据样本。以信号交叉口和路段作为建模单元,利用广义估计方程负二项回归模型研究了道路几何设计等交通相关因素对交通事故的影响,结果表明：信号交叉口交通事故起数与交通量、限速、主路中央分隔、主路行人过街设施、次路机非分隔、倒计时信号、交叉口夹角具有显著相关性；无控制出入路段交通事故起数与路段长度、车道数、限速、接入口密度、中央分隔以及公交车站设置有显著相关性。进一步探讨行人和非机动车保护设施与其他因素的交互安全效应发现：当交通量较大或位于居民区、高校区时,在路段和交叉口主路上设置人行横道与过街天桥组合型过街设施、在路段和交叉口次路上设置机非护栏分隔的安全效应最为显著。
收集了2004-2007年北京城市道路上机动车与自行车碰撞事故数据,以单起事故作为建模单元,对交通违法行为和事故严重程度的影响因素以及交通违法行为与事故形态的倾向关系进行分析。首先,利用多项logit回归模型分析了路口和路段上自行车和机动车主要交通违法行为与人口统计特征、道路几何设计等因素的显著相关性；其次,定义统计指标分析了机动车与自行车各类交通违法行为与不同事故形态的倾向关系,发现多数交通违法行为均显著对应于某些事故形态,其中侧面碰撞最为常见；最后,建立了机动车与自行车碰撞事故严重程度分析的二项logit回归模型,结果表明：正面和侧面碰撞、碾轧骑自行车人、夜间无路灯、道路无物理隔离、高限速、重型车辆以及高龄等因素与骑自行车人严重伤害显著相关。此外,研究还发现同向刮擦事故中发生碾轧骑自行车人的可能性最高。
通过问卷调查获取了武汉市248名出租车和公交车驾驶员的人口统计特征、风险感知、对危险驾驶的态度、异常驾驶行为以及事故发生情况等信息。方差分析发现：两组驾驶员在风险感知、态度以及驾驶行为所有测量维度上无显著差异,故将两组样本合并；以单个驾驶员作为建模单元,建立了基于二项logit回归的驾驶员责任事故影响因素分析模型,研究发现：侵略性违规驾驶和一般性违规驾驶行为显著影响驾驶员责任事故的发生；在此基础上,利用通径模型研究了驾驶员风险感知和态度的具体测量维度与上述两类危险驾驶行为的因果结构关系,结果表明：“对违法驾驶的态度”对危险驾驶行为有显著的直接作用,而“主观事故概率评估”和“对事故危害的关注”两个风险感知维度则通过“对违法驾驶的态度”间接作用于两类危险驾驶行为。
研究结果不仅可用于改善道路和交通工程设施设计,为政府部门实施交通安全管理提供决策支持,还有助于针对机动车驾驶员设计交通安全教育项目,提高驾驶员的安全意识,从而改善城市道路交通安全状况。
With a rapid increase in motorization level, the situation of traffic safety on urban roads is becoming a critical issue. How to decrease traffic crashes and lessen their severity levels has attracted more and more attention. In consideration of the random characteristics of crash events, multi-statistical techniques can be well used to model the statistically significant relationships between risk factors and traffic crashes based on traffic crash and related data, and accordingly the countermeasures can be proposed. In light of the serious traffic safety concerns on urban roads, this dissertation conducted a suite of research, including crash frequency analyses, crash severity analyses, and risky traffic behavior analyses.
Using a number of statistical indicators, we performed a descriptive statistical analysis for urban traffic crashes that take place on different time, on different road types, at different intersections/segments, by different vehicle usage, as well as different crash categories. As a result, it was found that safety issues related to main and minor arterials, four-legged signalized intersections and road segments with unrestricted access, taxis and buses, and vehicle-bicycle crashes are worth concerning.
With a review of studies on traffic crash analyses, this study developed a conception model for analyzing urban traffic crashes using multivariate statistical techniques, and designed a crash analysis framework aiming at the serious safety concerns shown above. The detailed analyses included are a crash frequency analysis of signalized intersections and road segments with unrestricted access on urban arterial network, a comprehensive analysis of vehicle-bicycle crashes, and a safety analysis of influential paths from psychology characteristics, driving behavior, to crashes for taxi and bus drivers.
A total of 108 four-legged signalized intersections and 123.5 km of urban roads were selected from the arterial network of Beijing. Severe crashes which occurred at the selected sites in a period of four years, as well as traffic-related information were collected to construct a longitudinal data set. Taking one site as a modeling unit, this study used the Generalized Estimating Equations modeling technique with a Negative Binomial link function to analyze significant effects of traffic-related factors on severe crashes. Results show that the arterial roads with heavier traffic, more road lanes and higher speed limits tend to have more severe crashes. Medians are helpful in reducing severe crashes. Moreover, higher severe crash risk is generally associated with intersections with small angle and countdown signal, and road segments with higher side access density and presence of bus stops. With regard to interaction effects between non-motorist protection facilities and other factors, results reveal that a combined use of crosswalk and overpass is the most desired pedestrian crossing facility for safety, especially at sites with heavy traffic or sites located at primarily residential areas. Furthermore, barriers separating bikeway and roadway on road segments or the minor roads of intersections are found effective to improve safety.
The comprehensive analysis of motor vehicle-bicycle crashes was conducted using 4 years of crash records (2004-2007) from Beijing. In this study, one crash is used as a modeling unit. Firstly, a multinomial logit model was used to associate non-compliant behaviors with demographics, geometric design, and other related factors, and it was found different non-compliant behaviors are correlated with a number of risk factors at different road locations. Secondly, with an analysis of propensities of non-compliant behaviors to different crash patterns, the results show angle collisions are the leading pattern of motor vehicle-bicycle crashes, and different non-compliant behaviors may lead to some specific crash patterns such as head-on or rear-end crashes. Thirdly, a binary logit model was employed to identify risk factors affecting bicyclist injury severity outcomes, and it was found bicyclist severe injuries are associated with head-on and angle collisions, occurrence of running over bicyclists, night without streetlight, roads without median/division, higher speed limit, heavy vehicle involvement and older bicyclists. Moreover, it was found orthokinetic scrape is more likely to result in running over bicyclists.
The safety analysis of taxi and bus drivers was based on the data obtained from a questionnaire survey carried out among 248 taxi and bus drivers in Wuhan. Firstly, One-way ANOVA was used to explore the difference between taxi and bus driver groups on all measuring scales, and there were no significant differences found. Hence, the survey data related to the drivers were aggregated. Secondly, a binary logit model was employed to analyze significant factors affecting driver at-fault crash occurrence, and results show that drivers who reported more tendencies of aggressive violations and ordinary violations, and who had previously been involved in at-fault crashes are in high risks of crash involvement. Thirdly, by developing a path model to analyze the casual relationships among risk perception, risk-taking attitudes, and risky driving behaviors, it was found that drivers' attitude towards rule violations has significant impact on risky driving behaviors. Furthermore, two risk perception scales, i.e. likelihood of crash and concern, have significantly indirect effects on the risky driving behavior through their influence on drivers'attitude towards rule violations.
The significant contributing factors identified in this study are expected to result in better designing of road and traffic facilities, better actualizing of traffic management for the safety, and better planning of road safety campaigns for vehicle drivers.
为了明确城市道路的突出交通安全问题,利用多项事故统计指标对城市道路交通事故在不同时间、不同道路类型、不同路口路段类型、不同车辆使用性质以及不同事故类型上的分布特征进行了描述性统计分析,发现主干路和次干路、四叉信号交叉口和无控制出入路段、出租和公交客运的交通安全问题,以及机动车与自行车碰撞事故值得关注。
在总结国内外道路交通事故分析研究的基础上,提出了城市道路交通事故分析概念模型,并结合上述交通安全突出问题,设计了城市道路交通事故分析体系,具体包括三个方面：城市干道网络中信号交叉口和无控制出入路段事故发生频次分析、城市道路机动车与自行车碰撞事故分析以及城市道路公共运输驾驶员“心理-行为-事故”影响链分析。
随机选取北京市城市干道网络中108个四叉信号交叉口和123.5 km无控制出入路段,收集了4年的轻伤及以上伤亡事故和相关交通因素信息,构建了纵向数据样本。以信号交叉口和路段作为建模单元,利用广义估计方程负二项回归模型研究了道路几何设计等交通相关因素对交通事故的影响,结果表明：信号交叉口交通事故起数与交通量、限速、主路中央分隔、主路行人过街设施、次路机非分隔、倒计时信号、交叉口夹角具有显著相关性；无控制出入路段交通事故起数与路段长度、车道数、限速、接入口密度、中央分隔以及公交车站设置有显著相关性。进一步探讨行人和非机动车保护设施与其他因素的交互安全效应发现：当交通量较大或位于居民区、高校区时,在路段和交叉口主路上设置人行横道与过街天桥组合型过街设施、在路段和交叉口次路上设置机非护栏分隔的安全效应最为显著。
收集了2004-2007年北京城市道路上机动车与自行车碰撞事故数据,以单起事故作为建模单元,对交通违法行为和事故严重程度的影响因素以及交通违法行为与事故形态的倾向关系进行分析。首先,利用多项logit回归模型分析了路口和路段上自行车和机动车主要交通违法行为与人口统计特征、道路几何设计等因素的显著相关性；其次,定义统计指标分析了机动车与自行车各类交通违法行为与不同事故形态的倾向关系,发现多数交通违法行为均显著对应于某些事故形态,其中侧面碰撞最为常见；最后,建立了机动车与自行车碰撞事故严重程度分析的二项logit回归模型,结果表明：正面和侧面碰撞、碾轧骑自行车人、夜间无路灯、道路无物理隔离、高限速、重型车辆以及高龄等因素与骑自行车人严重伤害显著相关。此外,研究还发现同向刮擦事故中发生碾轧骑自行车人的可能性最高。
通过问卷调查获取了武汉市248名出租车和公交车驾驶员的人口统计特征、风险感知、对危险驾驶的态度、异常驾驶行为以及事故发生情况等信息。方差分析发现：两组驾驶员在风险感知、态度以及驾驶行为所有测量维度上无显著差异,故将两组样本合并；以单个驾驶员作为建模单元,建立了基于二项logit回归的驾驶员责任事故影响因素分析模型,研究发现：侵略性违规驾驶和一般性违规驾驶行为显著影响驾驶员责任事故的发生；在此基础上,利用通径模型研究了驾驶员风险感知和态度的具体测量维度与上述两类危险驾驶行为的因果结构关系,结果表明：“对违法驾驶的态度”对危险驾驶行为有显著的直接作用,而“主观事故概率评估”和“对事故危害的关注”两个风险感知维度则通过“对违法驾驶的态度”间接作用于两类危险驾驶行为。
研究结果不仅可用于改善道路和交通工程设施设计,为政府部门实施交通安全管理提供决策支持,还有助于针对机动车驾驶员设计交通安全教育项目,提高驾驶员的安全意识,从而改善城市道路交通安全状况。
With a rapid increase in motorization level, the situation of traffic safety on urban roads is becoming a critical issue. How to decrease traffic crashes and lessen their severity levels has attracted more and more attention. In consideration of the random characteristics of crash events, multi-statistical techniques can be well used to model the statistically significant relationships between risk factors and traffic crashes based on traffic crash and related data, and accordingly the countermeasures can be proposed. In light of the serious traffic safety concerns on urban roads, this dissertation conducted a suite of research, including crash frequency analyses, crash severity analyses, and risky traffic behavior analyses.
Using a number of statistical indicators, we performed a descriptive statistical analysis for urban traffic crashes that take place on different time, on different road types, at different intersections/segments, by different vehicle usage, as well as different crash categories. As a result, it was found that safety issues related to main and minor arterials, four-legged signalized intersections and road segments with unrestricted access, taxis and buses, and vehicle-bicycle crashes are worth concerning.
With a review of studies on traffic crash analyses, this study developed a conception model for analyzing urban traffic crashes using multivariate statistical techniques, and designed a crash analysis framework aiming at the serious safety concerns shown above. The detailed analyses included are a crash frequency analysis of signalized intersections and road segments with unrestricted access on urban arterial network, a comprehensive analysis of vehicle-bicycle crashes, and a safety analysis of influential paths from psychology characteristics, driving behavior, to crashes for taxi and bus drivers.
A total of 108 four-legged signalized intersections and 123.5 km of urban roads were selected from the arterial network of Beijing. Severe crashes which occurred at the selected sites in a period of four years, as well as traffic-related information were collected to construct a longitudinal data set. Taking one site as a modeling unit, this study used the Generalized Estimating Equations modeling technique with a Negative Binomial link function to analyze significant effects of traffic-related factors on severe crashes. Results show that the arterial roads with heavier traffic, more road lanes and higher speed limits tend to have more severe crashes. Medians are helpful in reducing severe crashes. Moreover, higher severe crash risk is generally associated with intersections with small angle and countdown signal, and road segments with higher side access density and presence of bus stops. With regard to interaction effects between non-motorist protection facilities and other factors, results reveal that a combined use of crosswalk and overpass is the most desired pedestrian crossing facility for safety, especially at sites with heavy traffic or sites located at primarily residential areas. Furthermore, barriers separating bikeway and roadway on road segments or the minor roads of intersections are found effective to improve safety.
The comprehensive analysis of motor vehicle-bicycle crashes was conducted using 4 years of crash records (2004-2007) from Beijing. In this study, one crash is used as a modeling unit. Firstly, a multinomial logit model was used to associate non-compliant behaviors with demographics, geometric design, and other related factors, and it was found different non-compliant behaviors are correlated with a number of risk factors at different road locations. Secondly, with an analysis of propensities of non-compliant behaviors to different crash patterns, the results show angle collisions are the leading pattern of motor vehicle-bicycle crashes, and different non-compliant behaviors may lead to some specific crash patterns such as head-on or rear-end crashes. Thirdly, a binary logit model was employed to identify risk factors affecting bicyclist injury severity outcomes, and it was found bicyclist severe injuries are associated with head-on and angle collisions, occurrence of running over bicyclists, night without streetlight, roads without median/division, higher speed limit, heavy vehicle involvement and older bicyclists. Moreover, it was found orthokinetic scrape is more likely to result in running over bicyclists.
The safety analysis of taxi and bus drivers was based on the data obtained from a questionnaire survey carried out among 248 taxi and bus drivers in Wuhan. Firstly, One-way ANOVA was used to explore the difference between taxi and bus driver groups on all measuring scales, and there were no significant differences found. Hence, the survey data related to the drivers were aggregated. Secondly, a binary logit model was employed to analyze significant factors affecting driver at-fault crash occurrence, and results show that drivers who reported more tendencies of aggressive violations and ordinary violations, and who had previously been involved in at-fault crashes are in high risks of crash involvement. Thirdly, by developing a path model to analyze the casual relationships among risk perception, risk-taking attitudes, and risky driving behaviors, it was found that drivers' attitude towards rule violations has significant impact on risky driving behaviors. Furthermore, two risk perception scales, i.e. likelihood of crash and concern, have significantly indirect effects on the risky driving behavior through their influence on drivers'attitude towards rule violations.
The significant contributing factors identified in this study are expected to result in better designing of road and traffic facilities, better actualizing of traffic management for the safety, and better planning of road safety campaigns for vehicle drivers.
引文
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