Road crash prediction models are very useful tools in highway safety, given their potential for determining both the crash frequency occurrence and the degree severity of crashes. Crash frequency refers to the predict...Road crash prediction models are very useful tools in highway safety, given their potential for determining both the crash frequency occurrence and the degree severity of crashes. Crash frequency refers to the prediction of the number of crashes that would occur on a specific road segment or intersection in a time period, while crash severity models generally explore the relationship between crash severity injury and the contributing factors such as driver behavior, vehicle characteristics, roadway geometry, and road-environment conditions. Effective interventions to reduce crash toll include design of safer infrastructure and incorporation of road safety features into land-use and transportation planning;improvement of vehicle safety features;improvement of post-crash care for victims of road crashes;and improvement of driver behavior, such as setting and enforcing laws relating to key risk factors, and raising public awareness. Despite the great efforts that transportation agencies put into preventive measures, the annual number of traffic crashes has not yet significantly decreased. For in-stance, 35,092 traffic fatalities were recorded in the US in 2015, an increase of 7.2% as compared to the previous year. With such a trend, this paper presents an overview of road crash prediction models used by transportation agencies and researchers to gain a better understanding of the techniques used in predicting road accidents and the risk factors that contribute to crash occurrence.展开更多
The quantity and severity of traffic accidents have increased with the development of machinery life and traffic growth in cities and roads in the past 50 years. Among the road users, pedestrians are the most vulnerab...The quantity and severity of traffic accidents have increased with the development of machinery life and traffic growth in cities and roads in the past 50 years. Among the road users, pedestrians are the most vulnerable groups to be exposed to high risks. Vehicle crashes with pedestrian are almost inevitable and cause injury or death to pedestrian. Crash investigation and statistical studies indicate that percentage of pedestrian deaths caused by vehicle accidents are much more than all deaths. A considerable amount of accidents occur at signalized and urban intersections which are the intensive crash places. Therefore in this paper appropriate models that could specify safety indicators have been indicated with existing information by characterized parametric and nonparametric variables for twenty signalized intersections. Categories and correlations of variables also have been investigated. Three models including Regression, Poisson, and Negative binomial with defined variables have been determined. T and chi square tests, calibration and comparison of variables have been done by curve fitting. The role of each parameter was specified in pedestrian crashes. Validating models had the following outcomes: Pedestrian crash prediction models were based on none linear relations at intersections. Predictable variables, developing extended linear models and also pedestrian crash prediction are on the basis of Negative binomial distribution which is used due to more data dispersion. As observed, the Negative binomial regression because of its more R2 correlation factor has more validity among other regression models such as linear regression and Poisson. Calibrated models are put into sensitivity analysis to study the effect of each previously mentioned parameter in overall performance. Hence much better perception of future transportation plans can be achieved by development of safety models at planning levels.展开更多
A significant proportion of urban crashes,especially serious and fatal crashes,occur at traffic signals.Many of the black-spots in both Australia and New Zealand cities occur at high volume and/or high-speed traffic s...A significant proportion of urban crashes,especially serious and fatal crashes,occur at traffic signals.Many of the black-spots in both Australia and New Zealand cities occur at high volume and/or high-speed traffic signals.Given this,crash reduction studies often focus on the major signalised intersections.However,there is limited information that links the phasing configuration,degree of saturation and overall cycle time to crashes.While a number of analysis tools are available for assessing the efficiency of intersections,there are very few tools that can assist engineers in assessing the safety effects of intersection upgrades and new intersections.Safety performance functions have been developed to help quantify the safety impact of various traffic signal phasing configurations and level of intersection congestion at low and high-speed traffic signals in New Zealand and Australia.Data from 238 signalised intersection sites in Auckland,Wellington,Christchurch,Hamilton,Dunedin and Melbourne was used to develop crash prediction models for key crash-causing movements at traffic signals.Different variables(road features)effect each crash type.The models indicate that the safety of intersections can be improved by longer cycle times and longer lost inter-green times,especially all-red time,using fully protected right turns and by extending the length of right turn bays.The exception is at intersections with lots of pedestrians where shorter cycle times are preferred as pedestrian crashes increase with longer wait times.A number of factors have a negative impact on safety including,free left turns,more approach lanes,intersection arms operating near or over capacity in peak periods and higher speed limits.展开更多
交通安全服务水平(level of service of safety,LOSS)是国内外交通安全研究领域的新概念,用来描述道路的交通安全状况和道路为交通参与者提供交通安全服务的一种质量指标。系统地介绍了交通安全服务水平的国内外研究现状、概念定义、应...交通安全服务水平(level of service of safety,LOSS)是国内外交通安全研究领域的新概念,用来描述道路的交通安全状况和道路为交通参与者提供交通安全服务的一种质量指标。系统地介绍了交通安全服务水平的国内外研究现状、概念定义、应用和研究内容,研究了分级指标的选取,提出了σ理论的交通安全服务水平划分方法,分级量化了我国平原和山区高速公路的交通安全服务水平。交通安全服务水平作为定量评价交通安全的一种新方法,不仅可以用来描述改善交通安全的潜力有多大,而且可以作为交通安全改造工程实施对象的参考。展开更多
文摘Road crash prediction models are very useful tools in highway safety, given their potential for determining both the crash frequency occurrence and the degree severity of crashes. Crash frequency refers to the prediction of the number of crashes that would occur on a specific road segment or intersection in a time period, while crash severity models generally explore the relationship between crash severity injury and the contributing factors such as driver behavior, vehicle characteristics, roadway geometry, and road-environment conditions. Effective interventions to reduce crash toll include design of safer infrastructure and incorporation of road safety features into land-use and transportation planning;improvement of vehicle safety features;improvement of post-crash care for victims of road crashes;and improvement of driver behavior, such as setting and enforcing laws relating to key risk factors, and raising public awareness. Despite the great efforts that transportation agencies put into preventive measures, the annual number of traffic crashes has not yet significantly decreased. For in-stance, 35,092 traffic fatalities were recorded in the US in 2015, an increase of 7.2% as compared to the previous year. With such a trend, this paper presents an overview of road crash prediction models used by transportation agencies and researchers to gain a better understanding of the techniques used in predicting road accidents and the risk factors that contribute to crash occurrence.
文摘The quantity and severity of traffic accidents have increased with the development of machinery life and traffic growth in cities and roads in the past 50 years. Among the road users, pedestrians are the most vulnerable groups to be exposed to high risks. Vehicle crashes with pedestrian are almost inevitable and cause injury or death to pedestrian. Crash investigation and statistical studies indicate that percentage of pedestrian deaths caused by vehicle accidents are much more than all deaths. A considerable amount of accidents occur at signalized and urban intersections which are the intensive crash places. Therefore in this paper appropriate models that could specify safety indicators have been indicated with existing information by characterized parametric and nonparametric variables for twenty signalized intersections. Categories and correlations of variables also have been investigated. Three models including Regression, Poisson, and Negative binomial with defined variables have been determined. T and chi square tests, calibration and comparison of variables have been done by curve fitting. The role of each parameter was specified in pedestrian crashes. Validating models had the following outcomes: Pedestrian crash prediction models were based on none linear relations at intersections. Predictable variables, developing extended linear models and also pedestrian crash prediction are on the basis of Negative binomial distribution which is used due to more data dispersion. As observed, the Negative binomial regression because of its more R2 correlation factor has more validity among other regression models such as linear regression and Poisson. Calibrated models are put into sensitivity analysis to study the effect of each previously mentioned parameter in overall performance. Hence much better perception of future transportation plans can be achieved by development of safety models at planning levels.
文摘A significant proportion of urban crashes,especially serious and fatal crashes,occur at traffic signals.Many of the black-spots in both Australia and New Zealand cities occur at high volume and/or high-speed traffic signals.Given this,crash reduction studies often focus on the major signalised intersections.However,there is limited information that links the phasing configuration,degree of saturation and overall cycle time to crashes.While a number of analysis tools are available for assessing the efficiency of intersections,there are very few tools that can assist engineers in assessing the safety effects of intersection upgrades and new intersections.Safety performance functions have been developed to help quantify the safety impact of various traffic signal phasing configurations and level of intersection congestion at low and high-speed traffic signals in New Zealand and Australia.Data from 238 signalised intersection sites in Auckland,Wellington,Christchurch,Hamilton,Dunedin and Melbourne was used to develop crash prediction models for key crash-causing movements at traffic signals.Different variables(road features)effect each crash type.The models indicate that the safety of intersections can be improved by longer cycle times and longer lost inter-green times,especially all-red time,using fully protected right turns and by extending the length of right turn bays.The exception is at intersections with lots of pedestrians where shorter cycle times are preferred as pedestrian crashes increase with longer wait times.A number of factors have a negative impact on safety including,free left turns,more approach lanes,intersection arms operating near or over capacity in peak periods and higher speed limits.
文摘交通安全服务水平(level of service of safety,LOSS)是国内外交通安全研究领域的新概念,用来描述道路的交通安全状况和道路为交通参与者提供交通安全服务的一种质量指标。系统地介绍了交通安全服务水平的国内外研究现状、概念定义、应用和研究内容,研究了分级指标的选取,提出了σ理论的交通安全服务水平划分方法,分级量化了我国平原和山区高速公路的交通安全服务水平。交通安全服务水平作为定量评价交通安全的一种新方法,不仅可以用来描述改善交通安全的潜力有多大,而且可以作为交通安全改造工程实施对象的参考。
文摘为探索高速公路出口事故发生的关键诱因,依托美国佛罗里达州24条高速公路上405个出口匝道的历史事故和道路交通数据,验证了出口匝道事故服从于对数正态分布.以匝道交通量、匝道长度和设计一致性(分别以平均半径、曲率变化率、运行速度差和运行速度变化率度量)为解释变量,以2004—2006年间事故数为因变量,建立了4个泊松对数正态事故预测模型,其中以速度变化率表征设计一致性的事故预测模型具有最好的拟合度.基于最优拟合度模型的弹性分析表明,运行速度变化率及匝道长度为关键因素;基于安全考虑,出口匝道速度变化率宜控制在20%以内,出口匝道极限最小长度不宜小于200 m,一般最小长度不宜小于400 m.
