Moisture damage in asphalt mixtures can cause early cracking and rutting failures due to the internal damage accumulated by the high internal pore pressures created at the aggregate-binder interface and/or within the ...Moisture damage in asphalt mixtures can cause early cracking and rutting failures due to the internal damage accumulated by the high internal pore pressures created at the aggregate-binder interface and/or within the binder phase by heavy traffic loads.Tensile strength ratio(TSR)test results have not been effective indicators of moisture susceptibility of the asphalt mixtures.Therefore,a reliable moisture conditioning method and moisture susceptibility test need to be developed and implemented to determine the possible longterm impact of several new additive technologies on pavement longevity.In this study,different tests and conditioning methods for moisture susceptibility quantification of asphalt mixtures were evaluated,and a new test method incorporating a color measuring device was also developed that could identify the impact of different anti-stripping agents and warm-mix additives on moisture susceptibility of asphalt mixtures.Results indicated that the moisture-induced stress tester(MIST)conditioned and vacuum conditioned samples showed similar susceptibility towards rutting and moisture.Moreover,the CTindex parameter was not found to correlate with the moisture susceptibility of the mixes.Based on the results of the laboratory investigations,this study recommends the use of a colorimeter in conjunction with the current TSR method to determine the adhesion and cohesion-related moisture susceptibility.展开更多
Drowsy driving has received comparatively less attention in traffic safety literature when compared to other safety issues,despite its devastating impact on society in terms of human life lost and associated economic ...Drowsy driving has received comparatively less attention in traffic safety literature when compared to other safety issues,despite its devastating impact on society in terms of human life lost and associated economic burdens.Therefore,this significant safety threat requires a thorough investigation.To address the temporal instability of factors contributing to crashes involving drowsy drivers,this paper divides the crash data into four time periods while capturing unobserved heterogeneity in the means and variances of random parameters.To explore the determinants affecting the severity of injuries sustained by drowsy drivers involved in single-vehicle crashes,injury outcomes are categorized into three groups:serious,moderate,and no injuries.Using four years of crash data from the state of Washington between 2013 and 2016,a wide range of factors were examined,including driver characteristics,roadway conditions,crash characteristics,vehicle conditions,lighting conditions,and temporal factors.The estimation results reveal that there is temporal instability in terms of the effect of determinants on injury severity across the years.However,some factors exhibit stable effects,such as female drivers,sober drivers,and non-hit-and-run crashes.Based on the findings of this study,decision-makers,traffic engineers,and traffic authorities can gain valuable knowledge and insights into the factors contributing to drowsy-related crashes,enabling them to make informed recommendations for safety countermeasures.展开更多
Despite the importance of heavy vehicles in Australia’s transportation system,little is known on the factors influencing injury severity from accidents involving a single heavy vehicle.Heavy vehicular crashes have be...Despite the importance of heavy vehicles in Australia’s transportation system,little is known on the factors influencing injury severity from accidents involving a single heavy vehicle.Heavy vehicular crashes have been one of the main causes of fatal injuries in Australia,and this raises safety concerns for transport authorities,insurance companies,and emergency services.Although there have been several potential attempts to identify the factors contributing to heavy vehicle crashes and injury severity,it is still necessary to reduce the number of traffic crashes and lower the fatality rate involving heavy vehicles.The aims of this study were investigating the effects of heavy trucks’presence in accidents on the injury severity level sustained by the vehicle driver and detecting the contributing factors that lead to specific injury severity levels.Fixed-and random-parameter ordered probit and logit models were applied for predicting the likelihood of three injury severity categories severe,moderate,and no injury based on data from crashes caused by heavy trucks in Victoria,Australia in 2012-2017.The results showed that the random-parameter ordered probit model performed better than the other models did.Twenty variables(i.e.,factors)were found to be significant,and 12 of them were found to have random parameters that were normally distributed.Since some of the investigated factors had different effects on the type of injury severity in Australia,this paper does not recommend generalizing the findings from other case studies.Based on the findings,Victoria state authorities can have insight and enhanced understanding of the specific factors that lead to various types of injury severity involving heavy trucks.Consequently,the safety of all road users,including heavy vehicle drivers,can be enhanced.展开更多
Bicycling has been actively promoted as a clean and efficient mode of commute.Besides,due to the personal and societal benefits it provides,it has been adopted by many city dwellers for short-distance trips.Despite th...Bicycling has been actively promoted as a clean and efficient mode of commute.Besides,due to the personal and societal benefits it provides,it has been adopted by many city dwellers for short-distance trips.Despite the integral role this active transport mode plays,it is unfortunately associated with a high risk of fatalities in the event of a traffic crash as they are not protected.Many studies have been conducted in several jurisdictions to examine the factors contributing to crashes involving these vulnerable road users.In the case of Louisiana which is currently experiencing increased cases of severe and fatal bicycleinvolved crashes,less attention has been paid to investigating the critical factors influencing bicyclist injury severity outcomes using more detailed data and advanced econometric modeling frameworks to help propose adequate policies to improve the safety of riders.Against this background,this study examined the key contributing factors influencing bicyclist injuries by using more detailed roadway crash data spanning 2010-2016 obtained from the state of Louisiana.The study then applies an advanced random parameter logit modeling with heterogeneity in means and variances to address the unobserved heterogeneity issue associated with traffic crash data.To overcome the imbalanced data issue,three major crash injury levels were used instead of the conventional five crash injury levels.Besides,the data groups classified under each injury level were compared for the final variable selection.The study found that distracted drivers,elderly bicyclists,careless operations,and riding in dark conditions increase the probability of having severe injuries in vehicle-bicyclist crashes.Moreover,the variables for straight-level roadways and city streets decrease the odds of severe injuries.The straight-level roadway may provide better sight distance for both drivers and bicyclists,and complex environments like city streets discourage crashes with severe injuries.展开更多
The effect of sealed or unsealed road pavements on motorist’s injury severities has not been extensively explored.This study collected a four-year crash dataset(2015–2018)from South Australia to explore this issue.T...The effect of sealed or unsealed road pavements on motorist’s injury severities has not been extensively explored.This study collected a four-year crash dataset(2015–2018)from South Australia to explore this issue.The data shows 3,812 and 1,086 crashes at sealed and unsealed pavement surfaces,respectively,during those years.This study examines the consequence of sealed and unsealed pavements on driver injury severity outcomes of motor vehicle crashes.A mixed logit model was developed by accounting for heterogeneity in means and variances of the random parameters.The variables were distributed among several categories:driver,temporal,spatial,roadway characteristics,crash type,vehicle type,and vehicle movement.Four random parameters were observed in the sealed model,whereas five parameters were in the unsealed one.Moreover,the sealed pavements model showed substantial heterogeneity in means of four of the random parameters,while the unsealed pavements model has some heterogeneity in both means and variances of some of the random parameters.Marginal effect results indicate that two indicator variables have enlarged the likelihood of driver severe injury consequences in sealed,alcohol involvement and posted speed limit>100 km/hr.Additionally,four other significant variables sustain the probability of severe injury outcomes at unsealed pavement like male drivers,middle-aged drivers,rollover crash types,and crashes at straight roads.Based on these variables,various countermeasures were recommended to enhance the safety of both types of pavements.展开更多
文摘Moisture damage in asphalt mixtures can cause early cracking and rutting failures due to the internal damage accumulated by the high internal pore pressures created at the aggregate-binder interface and/or within the binder phase by heavy traffic loads.Tensile strength ratio(TSR)test results have not been effective indicators of moisture susceptibility of the asphalt mixtures.Therefore,a reliable moisture conditioning method and moisture susceptibility test need to be developed and implemented to determine the possible longterm impact of several new additive technologies on pavement longevity.In this study,different tests and conditioning methods for moisture susceptibility quantification of asphalt mixtures were evaluated,and a new test method incorporating a color measuring device was also developed that could identify the impact of different anti-stripping agents and warm-mix additives on moisture susceptibility of asphalt mixtures.Results indicated that the moisture-induced stress tester(MIST)conditioned and vacuum conditioned samples showed similar susceptibility towards rutting and moisture.Moreover,the CTindex parameter was not found to correlate with the moisture susceptibility of the mixes.Based on the results of the laboratory investigations,this study recommends the use of a colorimeter in conjunction with the current TSR method to determine the adhesion and cohesion-related moisture susceptibility.
文摘Drowsy driving has received comparatively less attention in traffic safety literature when compared to other safety issues,despite its devastating impact on society in terms of human life lost and associated economic burdens.Therefore,this significant safety threat requires a thorough investigation.To address the temporal instability of factors contributing to crashes involving drowsy drivers,this paper divides the crash data into four time periods while capturing unobserved heterogeneity in the means and variances of random parameters.To explore the determinants affecting the severity of injuries sustained by drowsy drivers involved in single-vehicle crashes,injury outcomes are categorized into three groups:serious,moderate,and no injuries.Using four years of crash data from the state of Washington between 2013 and 2016,a wide range of factors were examined,including driver characteristics,roadway conditions,crash characteristics,vehicle conditions,lighting conditions,and temporal factors.The estimation results reveal that there is temporal instability in terms of the effect of determinants on injury severity across the years.However,some factors exhibit stable effects,such as female drivers,sober drivers,and non-hit-and-run crashes.Based on the findings of this study,decision-makers,traffic engineers,and traffic authorities can gain valuable knowledge and insights into the factors contributing to drowsy-related crashes,enabling them to make informed recommendations for safety countermeasures.
文摘Despite the importance of heavy vehicles in Australia’s transportation system,little is known on the factors influencing injury severity from accidents involving a single heavy vehicle.Heavy vehicular crashes have been one of the main causes of fatal injuries in Australia,and this raises safety concerns for transport authorities,insurance companies,and emergency services.Although there have been several potential attempts to identify the factors contributing to heavy vehicle crashes and injury severity,it is still necessary to reduce the number of traffic crashes and lower the fatality rate involving heavy vehicles.The aims of this study were investigating the effects of heavy trucks’presence in accidents on the injury severity level sustained by the vehicle driver and detecting the contributing factors that lead to specific injury severity levels.Fixed-and random-parameter ordered probit and logit models were applied for predicting the likelihood of three injury severity categories severe,moderate,and no injury based on data from crashes caused by heavy trucks in Victoria,Australia in 2012-2017.The results showed that the random-parameter ordered probit model performed better than the other models did.Twenty variables(i.e.,factors)were found to be significant,and 12 of them were found to have random parameters that were normally distributed.Since some of the investigated factors had different effects on the type of injury severity in Australia,this paper does not recommend generalizing the findings from other case studies.Based on the findings,Victoria state authorities can have insight and enhanced understanding of the specific factors that lead to various types of injury severity involving heavy trucks.Consequently,the safety of all road users,including heavy vehicle drivers,can be enhanced.
文摘Bicycling has been actively promoted as a clean and efficient mode of commute.Besides,due to the personal and societal benefits it provides,it has been adopted by many city dwellers for short-distance trips.Despite the integral role this active transport mode plays,it is unfortunately associated with a high risk of fatalities in the event of a traffic crash as they are not protected.Many studies have been conducted in several jurisdictions to examine the factors contributing to crashes involving these vulnerable road users.In the case of Louisiana which is currently experiencing increased cases of severe and fatal bicycleinvolved crashes,less attention has been paid to investigating the critical factors influencing bicyclist injury severity outcomes using more detailed data and advanced econometric modeling frameworks to help propose adequate policies to improve the safety of riders.Against this background,this study examined the key contributing factors influencing bicyclist injuries by using more detailed roadway crash data spanning 2010-2016 obtained from the state of Louisiana.The study then applies an advanced random parameter logit modeling with heterogeneity in means and variances to address the unobserved heterogeneity issue associated with traffic crash data.To overcome the imbalanced data issue,three major crash injury levels were used instead of the conventional five crash injury levels.Besides,the data groups classified under each injury level were compared for the final variable selection.The study found that distracted drivers,elderly bicyclists,careless operations,and riding in dark conditions increase the probability of having severe injuries in vehicle-bicyclist crashes.Moreover,the variables for straight-level roadways and city streets decrease the odds of severe injuries.The straight-level roadway may provide better sight distance for both drivers and bicyclists,and complex environments like city streets discourage crashes with severe injuries.
文摘The effect of sealed or unsealed road pavements on motorist’s injury severities has not been extensively explored.This study collected a four-year crash dataset(2015–2018)from South Australia to explore this issue.The data shows 3,812 and 1,086 crashes at sealed and unsealed pavement surfaces,respectively,during those years.This study examines the consequence of sealed and unsealed pavements on driver injury severity outcomes of motor vehicle crashes.A mixed logit model was developed by accounting for heterogeneity in means and variances of the random parameters.The variables were distributed among several categories:driver,temporal,spatial,roadway characteristics,crash type,vehicle type,and vehicle movement.Four random parameters were observed in the sealed model,whereas five parameters were in the unsealed one.Moreover,the sealed pavements model showed substantial heterogeneity in means of four of the random parameters,while the unsealed pavements model has some heterogeneity in both means and variances of some of the random parameters.Marginal effect results indicate that two indicator variables have enlarged the likelihood of driver severe injury consequences in sealed,alcohol involvement and posted speed limit>100 km/hr.Additionally,four other significant variables sustain the probability of severe injury outcomes at unsealed pavement like male drivers,middle-aged drivers,rollover crash types,and crashes at straight roads.Based on these variables,various countermeasures were recommended to enhance the safety of both types of pavements.
