Background: Despite numerous studies demonstrating the effectiveness of Restricted Crossing U-Tur... more Background: Despite numerous studies demonstrating the effectiveness of Restricted Crossing U-Turn (RCUT) intersection design, its implementation remains uneven and close to zero in some large states, including California. This paper provides a comprehensive framework to estimate the operational and safety performance of future RCUT designs. The framework is demonstrated for a geometrically constrained intersection located on a high-speed rural expressway. The operational evaluation relies on microscopic simulation models of existing TWSC and alternate RCUT designs used to estimate network-wide performance measures. Methods: Two approaches are demonstrated for future safety estimation; first, an HSM-prescribed Empirical Bayes (EB) approach that uses Safety Performance Function (SPF) predictions combined with the crash history of the site. For typical applications, EB estimates may be combined with CMFs for RCUT found in the literature. This approach remains the preferred option for ...
Transportation Research Record: Journal of the Transportation Research Board
Vulnerable road users (VRUs, i.e., pedestrians and bicyclists) have seen an alarming rise in fata... more Vulnerable road users (VRUs, i.e., pedestrians and bicyclists) have seen an alarming rise in fatalities in recent years. School-age pedestrians in lower-income neighborhoods may be particularly at risk. This paper proposes a data-driven safe-systems approach to develop safety countermeasures for areas near elementary schools serving disadvantaged populations. A review of past literature on child-pedestrian training programs confirms that videos, lectures, and website-based training can provide children with vital information to improve their cognitive abilities relevant to walking safely. However, to improve pedestrian behavior on the road, children need to be safely exposed to traffic environments and practice interactions with traffic. Therefore, the use of virtual reality (VR) is recommended as a platform to introduce children to traffic interactions. Furthermore, the review of existing child-pedestrian training programs showed that most existing training programs (VR-based or ot...
This research has developed a child pedestrian training module using Virtual Reality (VR) system.... more This research has developed a child pedestrian training module using Virtual Reality (VR) system. Children can have an immersive experience of walking on streets in different street-crossing scenarios. Past literature and crash data analysis revealed higher and more severe injury cases for child pedestrians in school zones serving low-income and underrepresented communities. This training was developed to fulfill the needs for a child-pedestrian, living in such communities, to understand basic pedestrian rules and develop safe walking behavior. The training module has been created as a VR "game" where the child played the game as a "player". Each child experienced eight critical street-crossing scenarios named "levels" and numbered from 1 through 8. These levels are designed and developed based on crash data analysis to test the player's decision-making ability. A head-mounted device (HMD) was used to play the game, where a right-hand game controlle...
A training program was designed and developed for school-going children of 7-12 years old in orde... more A training program was designed and developed for school-going children of 7-12 years old in order to help them improve their understanding of safety rules at critical street-crossing scenarios. The training is constructed of two modules that take place on two different platforms. The first one is a bilingual instruction-based video presentation that demonstrates street crossing safety rules and is viewed on a digital display. The second one (virtual "game" ) takes place in a virtual environment (VE), and the trainee wears a virtual reality (VR) head-mounted device (Oculus Quest) to physically walk on 30-ft long marked and unmarked crosswalks to put the lesson into practice. Eight types of scenarios called "levels" were developed to test and improve the player's decision-making ability. In addition, an experiment was designed to test the efficacy of the program. Trials were run, where a participant watched the video presentation between the two times they wer...
Trucking industry is considered a driving force for logistic and supply chain systems which indir... more Trucking industry is considered a driving force for logistic and supply chain systems which indirectly influences the national economy. So, any impedance in truck-flow or supply chain system eventually brings substantial consequences in terms of monetary values. As such, a growing concern related to large-truck (Gross Vehicle Weight Rating (GVWR) greater than 10,000 pounds) crashes has increased in recent years due to the potential economic impacts and level of injury severity sustained. With this in mind, this study aims to analyze the injury severities of multi-vehicle collisions involving large-trucks through an advanced econometric modeling approach to shed light on the contributing factors leading to large-truck crashes. Through a fused national crash datasets, we hope to provide a clearer understanding of the complex interactions of contributing factors (e.g., factors related to human (drivers), vehicle, and road-environment) influencing multi-vehicle crash outcomes. To captur...
INTRODUCTION Medium to large truck crashes, particularly on rural curved roadways, lead to a disp... more INTRODUCTION Medium to large truck crashes, particularly on rural curved roadways, lead to a disproportionately higher number of fatalities and serious injuries relative to other passenger vehicles over time. The intent of this study is to identify and quantify the factors affecting injury severity outcomes for single-vehicle truck crashes on rural curved segments in North Carolina. The crash data were extracted from the Highway Safety Information System (HSIS) from 2010 to 2017. METHOD This study applied a mixed logit with heterogeneity in means and variances approach to model driver injury severity. The approach accounts for possible unobserved heterogeneity in the data resulting from driver, roadway, vehicle, traffic characteristics and/or environmental conditions. Results' Conclusion: The model results indicate that there is a complex interaction of driver characteristics such as demographics (male and female drivers, age below 30 years, and age between 50 to 65 years), driver physical condition (normal driving condition and sleepy while driving), driver actions (unsafe speed, overcorrection, and careless driving), restraint usage (lap-shoulder belt usage and unbelted), roadway and traffic characteristics (undivided road, medium right shoulder width, graded surface, low and medium speed limit, low traffic volume), environmental conditions (rainy condition), vehicle characteristics (tractor-trailer and semi-trailer), and crashes characteristics (fixed object crashes and rollover crashes). In addition, this study compared the contributing factor leading to driver injury severity for curved and straight rural segments. Practical Applications: The results clearly indicate the importance of driving behavior, such as, exceeding the speed limit and careless driving along the high-speed curved segments, need to be prioritized for the trucking agency. Similarly, the suggested countermeasures for roadway design and maintenance agency encompass warning signs and advisory speed limit, roadside barrier with chevrons, and edge line rumble strips are important concerning curved segments in rural highways.
Transportation Research Record: Journal of the Transportation Research Board, 2020
Roadway departure crashes are one of the core emphasis areas in Strategic Highway Safety Plans (S... more Roadway departure crashes are one of the core emphasis areas in Strategic Highway Safety Plans (SHSP). These crashes, especially on rural roads, lead to a disproportionately higher number of fatalities and serious injuries. The focus of this study is to identify and quantify the factors affecting injury-severity outcomes for single-vehicle roadway departure (SV-RwD) crashes on rural curved segments in Minnesota. The crash data are extracted from the Highway Safety Information System (HSIS) from 2010 to 2014. This study applied a mixed logit with heterogeneity in means and variances approach to model driver-injury severity. The approach accounts for possible unobserved heterogeneity in the data resulting from driver, roadway, traffic, environmental conditions, or any combination of these attributes. This analysis adds value to the growing body of literature because it uncovers some unobserved heterogeneity in the form the attributes specific to driver-injury severities in contrast to...
Transportation Research Record: Journal of the Transportation Research Board, 2013
Concern related to crashes that involve large trucks has increased in Texas recently because of t... more Concern related to crashes that involve large trucks has increased in Texas recently because of the potential economic impacts and level of injury severity that can be sustained. However, detailed studies on large truck crashes that highlight the contributing factors leading to injury severity have not been conducted in Texas, especially for its Interstate system. The contributing factors related to injury severity were analyzed with Texas crash data based on a discrete outcome-based model that accounts for possible unobserved heterogeneity related to human, vehicle, and road–environment factors. A random parameter logit (i.e., mixed logit) model was estimated to predict the likelihood of five standard injury severity scales commonly used in the Crash Records Information System in Texas: fatal, incapacitating, nonincapacitating, possible, and none (i.e., property damage only). Estimation results indicated that the level of injury severity outcomes was highly influenced by several co...
In recent years, a growing concern related to large truck accidents has increased owing to the le... more In recent years, a growing concern related to large truck accidents has increased owing to the level of injury severity that can be sustained and to the related potential economic impact. Current studies related to large truck-involved crashes are scarce and do not address the human factors that can greatly influence accident outcomes. This study presents an analysis of data from the fusion of several national data sets addressing injury severity related to large truck-involved crashes. This is accomplished by considering human, road environment, and vehicular factors in large truck-involved crashes on U.S. interstates. A random-parameter ordered-probit model was estimated to predict the likelihood of five injury severity outcomes-fatality, incapacitating, nonincapacitating, possible injury, and no injury. The modeling approach accounts for possible unobserved effects relating to human, vehicular, and road environment factors not present in the data. Estimation findings indicate that the level of injury severity is highly influenced by a number of complex interactions between factors, and the effects of some factors can vary across observations.
Abstract: This paper uses aggregate data from the World Health Organization (WHO) and Internation... more Abstract: This paper uses aggregate data from the World Health Organization (WHO) and International Road Federation (IRF) to identify the relationship between road traffic safety, health service levels, motorization level, and associated factors. To do this, two alternative ...
Background: Despite numerous studies demonstrating the effectiveness of Restricted Crossing U-Tur... more Background: Despite numerous studies demonstrating the effectiveness of Restricted Crossing U-Turn (RCUT) intersection design, its implementation remains uneven and close to zero in some large states, including California. This paper provides a comprehensive framework to estimate the operational and safety performance of future RCUT designs. The framework is demonstrated for a geometrically constrained intersection located on a high-speed rural expressway. The operational evaluation relies on microscopic simulation models of existing TWSC and alternate RCUT designs used to estimate network-wide performance measures. Methods: Two approaches are demonstrated for future safety estimation; first, an HSM-prescribed Empirical Bayes (EB) approach that uses Safety Performance Function (SPF) predictions combined with the crash history of the site. For typical applications, EB estimates may be combined with CMFs for RCUT found in the literature. This approach remains the preferred option for ...
Transportation Research Record: Journal of the Transportation Research Board
Vulnerable road users (VRUs, i.e., pedestrians and bicyclists) have seen an alarming rise in fata... more Vulnerable road users (VRUs, i.e., pedestrians and bicyclists) have seen an alarming rise in fatalities in recent years. School-age pedestrians in lower-income neighborhoods may be particularly at risk. This paper proposes a data-driven safe-systems approach to develop safety countermeasures for areas near elementary schools serving disadvantaged populations. A review of past literature on child-pedestrian training programs confirms that videos, lectures, and website-based training can provide children with vital information to improve their cognitive abilities relevant to walking safely. However, to improve pedestrian behavior on the road, children need to be safely exposed to traffic environments and practice interactions with traffic. Therefore, the use of virtual reality (VR) is recommended as a platform to introduce children to traffic interactions. Furthermore, the review of existing child-pedestrian training programs showed that most existing training programs (VR-based or ot...
This research has developed a child pedestrian training module using Virtual Reality (VR) system.... more This research has developed a child pedestrian training module using Virtual Reality (VR) system. Children can have an immersive experience of walking on streets in different street-crossing scenarios. Past literature and crash data analysis revealed higher and more severe injury cases for child pedestrians in school zones serving low-income and underrepresented communities. This training was developed to fulfill the needs for a child-pedestrian, living in such communities, to understand basic pedestrian rules and develop safe walking behavior. The training module has been created as a VR "game" where the child played the game as a "player". Each child experienced eight critical street-crossing scenarios named "levels" and numbered from 1 through 8. These levels are designed and developed based on crash data analysis to test the player's decision-making ability. A head-mounted device (HMD) was used to play the game, where a right-hand game controlle...
A training program was designed and developed for school-going children of 7-12 years old in orde... more A training program was designed and developed for school-going children of 7-12 years old in order to help them improve their understanding of safety rules at critical street-crossing scenarios. The training is constructed of two modules that take place on two different platforms. The first one is a bilingual instruction-based video presentation that demonstrates street crossing safety rules and is viewed on a digital display. The second one (virtual "game" ) takes place in a virtual environment (VE), and the trainee wears a virtual reality (VR) head-mounted device (Oculus Quest) to physically walk on 30-ft long marked and unmarked crosswalks to put the lesson into practice. Eight types of scenarios called "levels" were developed to test and improve the player's decision-making ability. In addition, an experiment was designed to test the efficacy of the program. Trials were run, where a participant watched the video presentation between the two times they wer...
Trucking industry is considered a driving force for logistic and supply chain systems which indir... more Trucking industry is considered a driving force for logistic and supply chain systems which indirectly influences the national economy. So, any impedance in truck-flow or supply chain system eventually brings substantial consequences in terms of monetary values. As such, a growing concern related to large-truck (Gross Vehicle Weight Rating (GVWR) greater than 10,000 pounds) crashes has increased in recent years due to the potential economic impacts and level of injury severity sustained. With this in mind, this study aims to analyze the injury severities of multi-vehicle collisions involving large-trucks through an advanced econometric modeling approach to shed light on the contributing factors leading to large-truck crashes. Through a fused national crash datasets, we hope to provide a clearer understanding of the complex interactions of contributing factors (e.g., factors related to human (drivers), vehicle, and road-environment) influencing multi-vehicle crash outcomes. To captur...
INTRODUCTION Medium to large truck crashes, particularly on rural curved roadways, lead to a disp... more INTRODUCTION Medium to large truck crashes, particularly on rural curved roadways, lead to a disproportionately higher number of fatalities and serious injuries relative to other passenger vehicles over time. The intent of this study is to identify and quantify the factors affecting injury severity outcomes for single-vehicle truck crashes on rural curved segments in North Carolina. The crash data were extracted from the Highway Safety Information System (HSIS) from 2010 to 2017. METHOD This study applied a mixed logit with heterogeneity in means and variances approach to model driver injury severity. The approach accounts for possible unobserved heterogeneity in the data resulting from driver, roadway, vehicle, traffic characteristics and/or environmental conditions. Results' Conclusion: The model results indicate that there is a complex interaction of driver characteristics such as demographics (male and female drivers, age below 30 years, and age between 50 to 65 years), driver physical condition (normal driving condition and sleepy while driving), driver actions (unsafe speed, overcorrection, and careless driving), restraint usage (lap-shoulder belt usage and unbelted), roadway and traffic characteristics (undivided road, medium right shoulder width, graded surface, low and medium speed limit, low traffic volume), environmental conditions (rainy condition), vehicle characteristics (tractor-trailer and semi-trailer), and crashes characteristics (fixed object crashes and rollover crashes). In addition, this study compared the contributing factor leading to driver injury severity for curved and straight rural segments. Practical Applications: The results clearly indicate the importance of driving behavior, such as, exceeding the speed limit and careless driving along the high-speed curved segments, need to be prioritized for the trucking agency. Similarly, the suggested countermeasures for roadway design and maintenance agency encompass warning signs and advisory speed limit, roadside barrier with chevrons, and edge line rumble strips are important concerning curved segments in rural highways.
Transportation Research Record: Journal of the Transportation Research Board, 2020
Roadway departure crashes are one of the core emphasis areas in Strategic Highway Safety Plans (S... more Roadway departure crashes are one of the core emphasis areas in Strategic Highway Safety Plans (SHSP). These crashes, especially on rural roads, lead to a disproportionately higher number of fatalities and serious injuries. The focus of this study is to identify and quantify the factors affecting injury-severity outcomes for single-vehicle roadway departure (SV-RwD) crashes on rural curved segments in Minnesota. The crash data are extracted from the Highway Safety Information System (HSIS) from 2010 to 2014. This study applied a mixed logit with heterogeneity in means and variances approach to model driver-injury severity. The approach accounts for possible unobserved heterogeneity in the data resulting from driver, roadway, traffic, environmental conditions, or any combination of these attributes. This analysis adds value to the growing body of literature because it uncovers some unobserved heterogeneity in the form the attributes specific to driver-injury severities in contrast to...
Transportation Research Record: Journal of the Transportation Research Board, 2013
Concern related to crashes that involve large trucks has increased in Texas recently because of t... more Concern related to crashes that involve large trucks has increased in Texas recently because of the potential economic impacts and level of injury severity that can be sustained. However, detailed studies on large truck crashes that highlight the contributing factors leading to injury severity have not been conducted in Texas, especially for its Interstate system. The contributing factors related to injury severity were analyzed with Texas crash data based on a discrete outcome-based model that accounts for possible unobserved heterogeneity related to human, vehicle, and road–environment factors. A random parameter logit (i.e., mixed logit) model was estimated to predict the likelihood of five standard injury severity scales commonly used in the Crash Records Information System in Texas: fatal, incapacitating, nonincapacitating, possible, and none (i.e., property damage only). Estimation results indicated that the level of injury severity outcomes was highly influenced by several co...
In recent years, a growing concern related to large truck accidents has increased owing to the le... more In recent years, a growing concern related to large truck accidents has increased owing to the level of injury severity that can be sustained and to the related potential economic impact. Current studies related to large truck-involved crashes are scarce and do not address the human factors that can greatly influence accident outcomes. This study presents an analysis of data from the fusion of several national data sets addressing injury severity related to large truck-involved crashes. This is accomplished by considering human, road environment, and vehicular factors in large truck-involved crashes on U.S. interstates. A random-parameter ordered-probit model was estimated to predict the likelihood of five injury severity outcomes-fatality, incapacitating, nonincapacitating, possible injury, and no injury. The modeling approach accounts for possible unobserved effects relating to human, vehicular, and road environment factors not present in the data. Estimation findings indicate that the level of injury severity is highly influenced by a number of complex interactions between factors, and the effects of some factors can vary across observations.
Abstract: This paper uses aggregate data from the World Health Organization (WHO) and Internation... more Abstract: This paper uses aggregate data from the World Health Organization (WHO) and International Road Federation (IRF) to identify the relationship between road traffic safety, health service levels, motorization level, and associated factors. To do this, two alternative ...
Uploads
Papers by Mouyid Islam