Albeit with the notable benefits associated with Dirichlet crash frequency models and spatial ones,there is little research dedicated to exploring their combined advantages.Such ensemble approach could be a viable alt...Albeit with the notable benefits associated with Dirichlet crash frequency models and spatial ones,there is little research dedicated to exploring their combined advantages.Such ensemble approach could be a viable alternative to existing models as it accounts for the unobserved heterogeneity by relaxing the constraints of specific distribution placed on the intercept while addressing the spatial correlations among roadway entities.To fill this gap,the authors aimed to develop Dirichlet semi-parametric models over the overdispersed generalized linear model framework while also incorporating spatially structured random effects using a distance-based weight matrix.Five models were developed which include four semi-parametric with flexible intercept and one parametric base model for comparison purposes.The four semi-parametric models entailed two models with a popular specification of stick-breaking Dirichlet process(DP)and two models with an alternative approach of Dirichlet distribution(DD),which are first applied in the field of traffic safety.All four models were estimated for mixture of points(discrete)and mixture of normals(continuous).The posterior density plots for the precision parameter justified the employment of the flexible Dirichlet approach to fit the crash data and supported the assumed prior for the precision parameter.All four Dirichlet models demonstrated the presence of distinct subpopulations suggesting that the intercepts of the models were not generated from a common distribution.The DP model based on mixture of normals illustrated better performance indicating its potential superiority to fit both insample and out-of-sample crash data.This finding indicated that the approach of continuous densities,unlike discrete points,may lend more flexibility to fit the data.展开更多
Intersection-related crashes are associated with high proportion of accidents involving drivers, occupants, pedestrians, and cyclists. In general, the purpose of intersection safety analysis is to determine the impact...Intersection-related crashes are associated with high proportion of accidents involving drivers, occupants, pedestrians, and cyclists. In general, the purpose of intersection safety analysis is to determine the impact of safety-related variables on pedestrians, cyclists and vehicles, so as to facilitate the design of effective and efficient countermeasure strategies to improve safety at intersections. This study investigates the effects of traffic, environ- mental, intersection geometric and pavement-related characteristics on total crash fre- quencies at intersections. A random-parameter Poisson model was used with crash data from 357 signalized intersections in Chicago from 2004 to 2010. The results indicate that out of the identified factors, evening peak period traffic volume, pavement condition, and unlighted intersections have the greatest effects on crash frequencies. Overall, the results seek to suggest that, in order to improve effective highway-related safety countermeasures at intersections, significant attention must be focused on ensuring that pavements are adequately maintained and intersections should be well lighted. It needs to be mentioned that, projects could be implemented at and around the study intersections during the study period （7 years）, which could affect the crash frequency over the time. This is an important variable which could be a part of the future studies to investigate the impacts of safety related works at intersections and their marginal effects on crash frequency at signalized intersections.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
The empirical Bayes(EB)method based on parametric statistical models such as the negative binomial(NB)has been widely used for ranking sites in the road network safety screening process.In this paper a novel non-param...The empirical Bayes(EB)method based on parametric statistical models such as the negative binomial(NB)has been widely used for ranking sites in the road network safety screening process.In this paper a novel non-parametric EB method for modeling crash frequency data based on Conditional Generative Adversarial Networks(CGAN)is proposed and evaluated over a real-world crash data set.Unlike parametric approaches,there is no need for a pre-specified underlying relationship between dependent and independent variables in the proposed CGAN-EB and they are able to model any types of distributions.The proposed methodology is applied to real-world and simulated crash data sets.The performance of CGAN-EB in terms of model fit,predictive performance and network screening outcomes is compared with the conventional approach(NB-EB)as a benchmark.The results indicate that the proposed CGAN-EB approach outperforms NB-EB in terms of prediction power and hotspot identification tests.展开更多
In 2014, 32,675 deaths were recorded in vehicle crashes within the United States. Out of these, 51% of the fatalities occurred in rural highways compared to 49% in urban highways. No specific crash data are available ...In 2014, 32,675 deaths were recorded in vehicle crashes within the United States. Out of these, 51% of the fatalities occurred in rural highways compared to 49% in urban highways. No specific crash data are available for the built-up areas along rural highways. Due to high fatalities in rural highways, it is important to identify the factors that cause the vehicle crashes. The main objective of this study is to determine the factors associated with se- verities of crashes that occurred in built-up areas along the rural highways of Nevada. Those factors could aid in making informed decisions while setting up speed zones in these built-up areas. Using descriptive statistics and binary logistic regression model, 337 crashes that occurred in 11 towns along the rural highways from 2002 to 2010 were analyzed. The results showed that more crashes occurred during favorable driving conditions, e.g., 87% crashes on dry roads and 70% crashes in clear weather. The binary logistic regression model showed that crashes occurred from midnight until 4 a.m. were 58.3% likely to be injury crashes rather than property damage only crashes, when other factors were kept at their mean values. Crashes on weekdays were three times more likely to be injury crashes than that occurred on weekends. When other factors were kept at their mean value, crashes involving motorcycles had an 80.2% probability of being injury crashes. Speeding was found to be 17 times more responsible for injury crashes than mechanical defects of the vehicle. As a result of this study, the Nevada Department of Transportation now can take various steps to improve public safety, including steps to reduce speeding and encourage the use of helmets for motorcycle riders.展开更多
This paper developed a traffic safety management system （TSMS） for improving safety on county paved roads in Wyoming. TSMS is a strategic and systematic process to improve safety of roadway network. When funding is ...This paper developed a traffic safety management system （TSMS） for improving safety on county paved roads in Wyoming. TSMS is a strategic and systematic process to improve safety of roadway network. When funding is limited, it is important to identify the best combination of safety improvement projects to provide the most benefits to society in terms of crash reduction. The factors included in the proposed optimization model are annual safety budget, roadway inventory, roadway functional classification, historical crashes, safety improvement countermeasures, cost and crash reduction factors （CRFs） associated with safety improvement countermeasures, and average daily traffics （ADTs）. This paper demonstrated how the proposed model can identify the best combination of safety improvement projects to maximize the safety benefits in terms of reducing overall crash frequency. Although the proposed methodology was implemented on the county paved road network of Wyoming, it could be easily modified for potential implementation on the Wyoming state highway system. Other states can also benefit by implementing a similar program within their jurisdictions.展开更多
This paper focuses on analysing the influence of geometric design characteristics on traffic safety using bi-directional data on a divided roadway operated under heterogeneous traffic conditions in India. The study wa...This paper focuses on analysing the influence of geometric design characteristics on traffic safety using bi-directional data on a divided roadway operated under heterogeneous traffic conditions in India. The study was carried out on a four lane divided inter-city highway in plain and rolling terrain. Statistical modelling approach by Poisson regression and Negative binomial regression were used to assess the safety performance as occurrence of crashes are random events and to identify the influence of the geometric design variables on the crash frequency. Negative binomial regression model was found to be more suitable to identify the variables contributing to road crashes. The study enabled better understanding of the factors related to road geometrics that influence road crash frequency. The study also established that operating speed has a significant contribution to the total number of crashes. Negative binomial models are found to be appropriate to predict road crashes on divided roadways under heterogeneous traffic conditions.展开更多
Safety performance functions(SPFs),or crash-prediction models,have played an important role in identifying the factors contributing to crashes,predicting crash counts and identifying hotspots.Since a great deal of tim...Safety performance functions(SPFs),or crash-prediction models,have played an important role in identifying the factors contributing to crashes,predicting crash counts and identifying hotspots.Since a great deal of time and effort is needed to estimate an SPF,previous studies have sought to determine the transferability of particular SPFs;that is,the extent to which they can be applied to data from other regions.Although many efforts have been made to examine micro-level SPF transferability,few studies have focused on macro-level SPF transferability.There has been little transferability analysis of macro-level SPFs in the international context,especially between western countries.This study therefore evaluates the transferability of SPFs for several states in the USA(Illinois,Florida and Colorado)and for Italy.The SPFs were developed using data from counties in the United States and provincias in Italy,and the results revealed multiple common significant variables between the two countries.Transferability indexes were then calculated between the SPFs.These showed that the Italy SPFs for total crashes and bicycle crashes were transferable to US data after calibration factors were applied,whereas the US SPFs for total and bicycle crashes,with the exception of the Colorado SPF,could not be transferred to the Italian data.On the other hand,none of the pedestrian SPFs developed was transferable to other countries.This paper provides insights into the applicability of macro-level SPFs between the USA and Italy,and shows a good potential for international SPF transferability.Nevertheless,further investigation is needed of SPF transferability between a wider range of countries.展开更多
文摘Albeit with the notable benefits associated with Dirichlet crash frequency models and spatial ones,there is little research dedicated to exploring their combined advantages.Such ensemble approach could be a viable alternative to existing models as it accounts for the unobserved heterogeneity by relaxing the constraints of specific distribution placed on the intercept while addressing the spatial correlations among roadway entities.To fill this gap,the authors aimed to develop Dirichlet semi-parametric models over the overdispersed generalized linear model framework while also incorporating spatially structured random effects using a distance-based weight matrix.Five models were developed which include four semi-parametric with flexible intercept and one parametric base model for comparison purposes.The four semi-parametric models entailed two models with a popular specification of stick-breaking Dirichlet process(DP)and two models with an alternative approach of Dirichlet distribution(DD),which are first applied in the field of traffic safety.All four models were estimated for mixture of points(discrete)and mixture of normals(continuous).The posterior density plots for the precision parameter justified the employment of the flexible Dirichlet approach to fit the crash data and supported the assumed prior for the precision parameter.All four Dirichlet models demonstrated the presence of distinct subpopulations suggesting that the intercepts of the models were not generated from a common distribution.The DP model based on mixture of normals illustrated better performance indicating its potential superiority to fit both insample and out-of-sample crash data.This finding indicated that the approach of continuous densities,unlike discrete points,may lend more flexibility to fit the data.
文摘Intersection-related crashes are associated with high proportion of accidents involving drivers, occupants, pedestrians, and cyclists. In general, the purpose of intersection safety analysis is to determine the impact of safety-related variables on pedestrians, cyclists and vehicles, so as to facilitate the design of effective and efficient countermeasure strategies to improve safety at intersections. This study investigates the effects of traffic, environ- mental, intersection geometric and pavement-related characteristics on total crash fre- quencies at intersections. A random-parameter Poisson model was used with crash data from 357 signalized intersections in Chicago from 2004 to 2010. The results indicate that out of the identified factors, evening peak period traffic volume, pavement condition, and unlighted intersections have the greatest effects on crash frequencies. Overall, the results seek to suggest that, in order to improve effective highway-related safety countermeasures at intersections, significant attention must be focused on ensuring that pavements are adequately maintained and intersections should be well lighted. It needs to be mentioned that, projects could be implemented at and around the study intersections during the study period （7 years）, which could affect the crash frequency over the time. This is an important variable which could be a part of the future studies to investigate the impacts of safety related works at intersections and their marginal effects on crash frequency at signalized intersections.
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The empirical Bayes(EB)method based on parametric statistical models such as the negative binomial(NB)has been widely used for ranking sites in the road network safety screening process.In this paper a novel non-parametric EB method for modeling crash frequency data based on Conditional Generative Adversarial Networks(CGAN)is proposed and evaluated over a real-world crash data set.Unlike parametric approaches,there is no need for a pre-specified underlying relationship between dependent and independent variables in the proposed CGAN-EB and they are able to model any types of distributions.The proposed methodology is applied to real-world and simulated crash data sets.The performance of CGAN-EB in terms of model fit,predictive performance and network screening outcomes is compared with the conventional approach(NB-EB)as a benchmark.The results indicate that the proposed CGAN-EB approach outperforms NB-EB in terms of prediction power and hotspot identification tests.
基金Nevada Department of Transportation(NDOT)for funding the studyprovided under grant#P255-11-803 by NDOT
文摘In 2014, 32,675 deaths were recorded in vehicle crashes within the United States. Out of these, 51% of the fatalities occurred in rural highways compared to 49% in urban highways. No specific crash data are available for the built-up areas along rural highways. Due to high fatalities in rural highways, it is important to identify the factors that cause the vehicle crashes. The main objective of this study is to determine the factors associated with se- verities of crashes that occurred in built-up areas along the rural highways of Nevada. Those factors could aid in making informed decisions while setting up speed zones in these built-up areas. Using descriptive statistics and binary logistic regression model, 337 crashes that occurred in 11 towns along the rural highways from 2002 to 2010 were analyzed. The results showed that more crashes occurred during favorable driving conditions, e.g., 87% crashes on dry roads and 70% crashes in clear weather. The binary logistic regression model showed that crashes occurred from midnight until 4 a.m. were 58.3% likely to be injury crashes rather than property damage only crashes, when other factors were kept at their mean values. Crashes on weekdays were three times more likely to be injury crashes than that occurred on weekends. When other factors were kept at their mean value, crashes involving motorcycles had an 80.2% probability of being injury crashes. Speeding was found to be 17 times more responsible for injury crashes than mechanical defects of the vehicle. As a result of this study, the Nevada Department of Transportation now can take various steps to improve public safety, including steps to reduce speeding and encourage the use of helmets for motorcycle riders.
基金the Wyoming LTAP Center for supporting this research study
文摘This paper developed a traffic safety management system （TSMS） for improving safety on county paved roads in Wyoming. TSMS is a strategic and systematic process to improve safety of roadway network. When funding is limited, it is important to identify the best combination of safety improvement projects to provide the most benefits to society in terms of crash reduction. The factors included in the proposed optimization model are annual safety budget, roadway inventory, roadway functional classification, historical crashes, safety improvement countermeasures, cost and crash reduction factors （CRFs） associated with safety improvement countermeasures, and average daily traffics （ADTs）. This paper demonstrated how the proposed model can identify the best combination of safety improvement projects to maximize the safety benefits in terms of reducing overall crash frequency. Although the proposed methodology was implemented on the county paved road network of Wyoming, it could be easily modified for potential implementation on the Wyoming state highway system. Other states can also benefit by implementing a similar program within their jurisdictions.
文摘This paper focuses on analysing the influence of geometric design characteristics on traffic safety using bi-directional data on a divided roadway operated under heterogeneous traffic conditions in India. The study was carried out on a four lane divided inter-city highway in plain and rolling terrain. Statistical modelling approach by Poisson regression and Negative binomial regression were used to assess the safety performance as occurrence of crashes are random events and to identify the influence of the geometric design variables on the crash frequency. Negative binomial regression model was found to be more suitable to identify the variables contributing to road crashes. The study enabled better understanding of the factors related to road geometrics that influence road crash frequency. The study also established that operating speed has a significant contribution to the total number of crashes. Negative binomial models are found to be appropriate to predict road crashes on divided roadways under heterogeneous traffic conditions.
文摘Safety performance functions(SPFs),or crash-prediction models,have played an important role in identifying the factors contributing to crashes,predicting crash counts and identifying hotspots.Since a great deal of time and effort is needed to estimate an SPF,previous studies have sought to determine the transferability of particular SPFs;that is,the extent to which they can be applied to data from other regions.Although many efforts have been made to examine micro-level SPF transferability,few studies have focused on macro-level SPF transferability.There has been little transferability analysis of macro-level SPFs in the international context,especially between western countries.This study therefore evaluates the transferability of SPFs for several states in the USA(Illinois,Florida and Colorado)and for Italy.The SPFs were developed using data from counties in the United States and provincias in Italy,and the results revealed multiple common significant variables between the two countries.Transferability indexes were then calculated between the SPFs.These showed that the Italy SPFs for total crashes and bicycle crashes were transferable to US data after calibration factors were applied,whereas the US SPFs for total and bicycle crashes,with the exception of the Colorado SPF,could not be transferred to the Italian data.On the other hand,none of the pedestrian SPFs developed was transferable to other countries.This paper provides insights into the applicability of macro-level SPFs between the USA and Italy,and shows a good potential for international SPF transferability.Nevertheless,further investigation is needed of SPF transferability between a wider range of countries.
