cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.27078051.v1
title: Assessing the impact of cannabis use on freeway driving performance and practices: A comparative analysis with placebo and alcohol-influenced driving

description: The objectives of this study were 1) to identify the effects cannabis has on driving performance and individual motor practices when on the freeway compared to placebo and 2) to bring context to the effects of cannabis on driving by comparing effect sizes to those of alcohol. Data for analysis was collected from a study of fifty-three participants with a history of tetrahydrocannabinol (THC) cannabis use who completed three visits in randomized order (placebo (0% THC), 6.18% THC, and 10.5% THC). Data for the alcohol analysis was from a subset of eighteen of these participants with a history of recent alcohol use that completed a fourth alcohol visit that targeted a .05 g/210L breath alcohol content (BrAC) during the drive. Comparisons were made using an analysis of variance approach with the SAS General Linear Models Procedure. Cohen’s <i>d</i> effect sizes were calculated for the cannabis and alcohol conditions relative to placebo for both the full sample and alcohol subset. Standard deviation of lane position (SDLP) for cannabis significantly increased compared to placebo and the effect size was comparable to that of alcohol at .05 BrAC. Lane departures for cannabis significantly increased relative to placebo as did the time out of the lane. Cannabis use resulted in an increased amount of time at 10% or more below the speed limit for the 6.18% THC condition. Relative to alcohol, cannabis produced more time at slower speeds and less time at speeds more than 10% above the speed limit. Multiple factors of lateral and longitudinal vehicle control on the freeway showed statistical significance. Drivers under the influence of cannabis exhibited higher rates of driving errors but also showed more cautious behaviors such as generally lower speeds on the freeway. Compared with alcohol, effect sizes varied. For longitudinal control, there were larger effect sizes for alcohol with speed effects in opposite directions, but relatively equivalent effect sizes for lateral control and driving errors associated with lane keeping.
DOI: 10.6084/m9.figshare.27111659
title: Evaluating the effectiveness of safety countermeasures at highway–railway grade crossing based on a machine learning framework

description: This research aims to cluster similar highway–railway grade crossings (HRGCs) to examine the safety countermeasures at HRGCs. The methodology integrates inventory and collision data from Federal Railroad Association (FRA) data set during years 2010 to 2022 . The XGBoost and random forest (RF) algorithms are employed to identify influential collision severity factors. Then, the deep latent class analysis (DLCA) method is utilized on selected inventory factors as important features to cluster similar HRGCs. Afterward, collision modification factor (CMF) and standard error (SE) measures are computed for each countermeasure through collisions within each HRGC cluster. XGBoost successfully identified 20 important collision and inventory factors with importance levels exceeding 94%, such as the number of daily trains and the surface material. Then, the DCLA method achieved 4 distinct clusters optimized by high similarity within each cluster and significant independence among clusters. The effectiveness of countermeasures was computed in terms of CMF and SE. The CMF results demonstrated that bells achieved superior safety compared to other countermeasures in clusters with sharper track angles and high maximum train speeds. Implementing bells decreased collisions across Clusters 1 and 4, with reductions of 53% (CMF = 0.47) and 46% (CMF = 0.54), respectively. The results highlight XGBoost’s capability to identify important collision and inventory factors, successfully uncovering 20 of the most important factors. The DCLA clustering method forms 4 distinct groups marked by substantial internal similarity within each cluster. This approach contributes to a clearer understanding of how each countermeasure impacts collision frequency. The findings highlight the varying effectiveness of different countermeasures across clusters, improving decision making for safety at HRGCs. The study highlights the efficacy of crossbucks in addressing safety concerns during moderate traffic conditions, particularly evident in environments with a highway speed limit between 100 and 125 mph. Additionally, bells demonstrate notable effectiveness in areas with sharper track angles.
DOI: 10.6084/m9.figshare.27111659.v1
title: Evaluating the effectiveness of safety countermeasures at highway–railway grade crossing based on a machine learning framework

description: This research aims to cluster similar highway–railway grade crossings (HRGCs) to examine the safety countermeasures at HRGCs. The methodology integrates inventory and collision data from Federal Railroad Association (FRA) data set during years 2010 to 2022 . The XGBoost and random forest (RF) algorithms are employed to identify influential collision severity factors. Then, the deep latent class analysis (DLCA) method is utilized on selected inventory factors as important features to cluster similar HRGCs. Afterward, collision modification factor (CMF) and standard error (SE) measures are computed for each countermeasure through collisions within each HRGC cluster. XGBoost successfully identified 20 important collision and inventory factors with importance levels exceeding 94%, such as the number of daily trains and the surface material. Then, the DCLA method achieved 4 distinct clusters optimized by high similarity within each cluster and significant independence among clusters. The effectiveness of countermeasures was computed in terms of CMF and SE. The CMF results demonstrated that bells achieved superior safety compared to other countermeasures in clusters with sharper track angles and high maximum train speeds. Implementing bells decreased collisions across Clusters 1 and 4, with reductions of 53% (CMF = 0.47) and 46% (CMF = 0.54), respectively. The results highlight XGBoost’s capability to identify important collision and inventory factors, successfully uncovering 20 of the most important factors. The DCLA clustering method forms 4 distinct groups marked by substantial internal similarity within each cluster. This approach contributes to a clearer understanding of how each countermeasure impacts collision frequency. The findings highlight the varying effectiveness of different countermeasures across clusters, improving decision making for safety at HRGCs. The study highlights the efficacy of crossbucks in addressing safety concerns during moderate traffic conditions, particularly evident in environments with a highway speed limit between 100 and 125 mph. Additionally, bells demonstrate notable effectiveness in areas with sharper track angles.
DOI: 10.6084/m9.figshare.27111649
title: An evaluation of front seat distance from rear facing child restraint systems in prevention of injury in frontal crash tests

description: Elevated head injury incidence in infants compared to toddlers involved as occupants in motor vehicle crashes has been demonstrated in multiple population-representative crash databases. Further, experimental studies have revealed a potential injury mechanism <i>via</i> impact between a rear-facing, CRS-restrained child and the back of the vehicle seat or console on the row in front of the CRS. Subsequently, experimental studies have suggested that bracing the CRS against the seat immediately in front of the CRS could mitigate head injury, but also indicated that more research was necessary. Thus, we investigated the effect of bracing against the front seat, as well as distance from the front seat with rear-facing infant carriers and rear-facing convertibles, with a focus on changes to measured head, neck and chest injury metrics in rear facing CRSs. Further, we examined the effect of using the infant carrier with and without a base on these injury metrics. 34 frontal sled tests at 30 or 35 mph were conducted using a simulated rear-row vehicle seat and structure representing the front seatback. A Q1.5 anthropomorphic test device (ATD) was placed in a single make/model LATCH-affixed rear-facing convertible or single make/model infant carrier; infant carrier without base was affixed with lap and shoulder belt. To evaluate the effect of bracing and distance, tests were conducted with a 300, 140, 70, or 15 mm gap between the CRS seatback and the front seatback, or a touching (0 mm) or braced (-20 mm) condition. Bayesian regression models quantified the effects of various predictors and model uncertainty. For tests with the convertible CRS, no head contact was observed between the head and the front vehicle seatback. For the infant carrier, head contact occurred at both 70 and 140 mm distances but not the other distances. On average, the −20, 0, or 15 mm distances yielded a 60% reduction in head injury criterion with 15 millisecond window (HIC15), and a 60% to 80% reduction in neck tension, compared to the 70 and 140 mm distances; chest acceleration also decreased for the convertible seat only. In the case of both carriers and convertibles, each mm of distance the CRS moves away from the front seatback up to 70 mm, adds 5.3 HIC15 points (95% Credible Interval (CrI):[4.6, 6.2]), and 3.5 Newtons (95% CrI: [2.2, 4.8]) of neck tension, on average. Placing a rear facing CRS, both convertibles and infant carriers, against or close to the seatback of the seat immediately in front of the CRS reduces head and tensile neck injury criteria in ATDs. The amount of gap between the front seat and the rear facing CRS is strongly and positively correlated with HIC for both convertibles and infant carriers. RF infant carriers with and without a base yield comparable injury metrics and kinematics when touching or nearly touching the back of the front vehicle seatback.
DOI: 10.6084/m9.figshare.27111649.v1
title: An evaluation of front seat distance from rear facing child restraint systems in prevention of injury in frontal crash tests

description: Elevated head injury incidence in infants compared to toddlers involved as occupants in motor vehicle crashes has been demonstrated in multiple population-representative crash databases. Further, experimental studies have revealed a potential injury mechanism <i>via</i> impact between a rear-facing, CRS-restrained child and the back of the vehicle seat or console on the row in front of the CRS. Subsequently, experimental studies have suggested that bracing the CRS against the seat immediately in front of the CRS could mitigate head injury, but also indicated that more research was necessary. Thus, we investigated the effect of bracing against the front seat, as well as distance from the front seat with rear-facing infant carriers and rear-facing convertibles, with a focus on changes to measured head, neck and chest injury metrics in rear facing CRSs. Further, we examined the effect of using the infant carrier with and without a base on these injury metrics. 34 frontal sled tests at 30 or 35 mph were conducted using a simulated rear-row vehicle seat and structure representing the front seatback. A Q1.5 anthropomorphic test device (ATD) was placed in a single make/model LATCH-affixed rear-facing convertible or single make/model infant carrier; infant carrier without base was affixed with lap and shoulder belt. To evaluate the effect of bracing and distance, tests were conducted with a 300, 140, 70, or 15 mm gap between the CRS seatback and the front seatback, or a touching (0 mm) or braced (-20 mm) condition. Bayesian regression models quantified the effects of various predictors and model uncertainty. For tests with the convertible CRS, no head contact was observed between the head and the front vehicle seatback. For the infant carrier, head contact occurred at both 70 and 140 mm distances but not the other distances. On average, the −20, 0, or 15 mm distances yielded a 60% reduction in head injury criterion with 15 millisecond window (HIC15), and a 60% to 80% reduction in neck tension, compared to the 70 and 140 mm distances; chest acceleration also decreased for the convertible seat only. In the case of both carriers and convertibles, each mm of distance the CRS moves away from the front seatback up to 70 mm, adds 5.3 HIC15 points (95% Credible Interval (CrI):[4.6, 6.2]), and 3.5 Newtons (95% CrI: [2.2, 4.8]) of neck tension, on average. Placing a rear facing CRS, both convertibles and infant carriers, against or close to the seatback of the seat immediately in front of the CRS reduces head and tensile neck injury criteria in ATDs. The amount of gap between the front seat and the rear facing CRS is strongly and positively correlated with HIC for both convertibles and infant carriers. RF infant carriers with and without a base yield comparable injury metrics and kinematics when touching or nearly touching the back of the front vehicle seatback.
DOI: 10.6084/m9.figshare.27111658
title: Age-related driver injury occurrence from crashes at curve–grade combined segments

description: Due to their relatively complex roadway characteristics, horizontal and vertical curve segments are associated with decreased visibility and a higher risk of rollovers. Multiple studies have identified the associated risk of young and older drivers separately in such complicated driving environments. This study investigated the relationship between driver age and injury occurrence from crashes occurring along curve–grade combined segments. Crash data recorded in Ohio State between 2012 and 2017 were used in this study. Driver age was categorized into 3 groups: teen (age &lt;20 years), adult (age 20–64), and older adult (age &gt;64). Descriptive statistics were summarized using random forest, gradient boosting, and extreme gradient boosting (XGBoost) to estimate the probability of a driver incurring an injury in case of a crash at curve–grade combined segments. The area under the receiver operating characteristics curve (AUROC) was used to select the best performing model. Partial dependence plots (PDPs) were used to interpret the model results. The probability of injury occurrence is different for older drivers compared to teen and adult drivers. Although teen and adult drivers showed a higher probability of sustaining injuries in crashes with an increase in the degree of curvature, older drivers were more likely to sustain injuries in roadways with higher annual average daily traffic (AADT), steeper grades, and more occupants in the vehicle. Older drivers were observed to have a higher probability of sustaining injuries during peak hours and when unrestrained compared to teen and adult drivers. The results emphasize the significance of tailored education and outreach countermeasures, particularly for teen and older drivers, aimed at decreasing the likelihood of injuries in such driving environments. This research adds to the expanding body of knowledge concerning the age-related occurrence of driver injuries resulting from crashes at curve–grade combined segments. The study findings provide insights into the potential over- or underrepresentation of certain age groups in analyzing crash injury occurrence. The insights gained from the machine learning analysis could also assist policymakers, transportation agencies, and traffic safety experts in developing targeted strategies to enhance road safety and protect vulnerable age groups.
DOI: 10.6084/m9.figshare.27111658.v1
title: Age-related driver injury occurrence from crashes at curve–grade combined segments

description: Due to their relatively complex roadway characteristics, horizontal and vertical curve segments are associated with decreased visibility and a higher risk of rollovers. Multiple studies have identified the associated risk of young and older drivers separately in such complicated driving environments. This study investigated the relationship between driver age and injury occurrence from crashes occurring along curve–grade combined segments. Crash data recorded in Ohio State between 2012 and 2017 were used in this study. Driver age was categorized into 3 groups: teen (age &lt;20 years), adult (age 20–64), and older adult (age &gt;64). Descriptive statistics were summarized using random forest, gradient boosting, and extreme gradient boosting (XGBoost) to estimate the probability of a driver incurring an injury in case of a crash at curve–grade combined segments. The area under the receiver operating characteristics curve (AUROC) was used to select the best performing model. Partial dependence plots (PDPs) were used to interpret the model results. The probability of injury occurrence is different for older drivers compared to teen and adult drivers. Although teen and adult drivers showed a higher probability of sustaining injuries in crashes with an increase in the degree of curvature, older drivers were more likely to sustain injuries in roadways with higher annual average daily traffic (AADT), steeper grades, and more occupants in the vehicle. Older drivers were observed to have a higher probability of sustaining injuries during peak hours and when unrestrained compared to teen and adult drivers. The results emphasize the significance of tailored education and outreach countermeasures, particularly for teen and older drivers, aimed at decreasing the likelihood of injuries in such driving environments. This research adds to the expanding body of knowledge concerning the age-related occurrence of driver injuries resulting from crashes at curve–grade combined segments. The study findings provide insights into the potential over- or underrepresentation of certain age groups in analyzing crash injury occurrence. The insights gained from the machine learning analysis could also assist policymakers, transportation agencies, and traffic safety experts in developing targeted strategies to enhance road safety and protect vulnerable age groups.
DOI: 10.6084/m9.figshare.27078054
title: Speed-securing measures on rural roads in Sweden: An observational study

description: Speed-securing measures are intended to, as the name suggests, to secure that the speeds of road users do not exceed the safe speed for a given type of environment. The purpose of this study was to make an evaluation of existing speed-securing measures on rural roads in Sweden to see how well they manage to limit the speed. A total of 34 unique locations have been filmed with drones with varying speed limits between 40 and 70 km/h. The analysis focused on the radius of both the individual vehicle trajectories and the radius of the roads themselves and how they relate to the speed choice of the drivers (including the 85th percentile speed). The result shows a moderate correlation between both types of radii and the speed choice of the drivers. In addition, the result also shows only a weak correlation between the driven radius and the radius of the roads themselves. Finally, the result also shows that only 17 locations manage to keep the 85th percentile speeds under the speed limit. Overall, the study suggests that the radius of the infrastructure is an important factor to lower the speed but the lack of a clear relationship between the driven radius and the radius of the road shows that more research is needed to properly understand why some locations work better than others.
DOI: 10.6084/m9.figshare.27078054.v1
title: Speed-securing measures on rural roads in Sweden: An observational study

description: Speed-securing measures are intended to, as the name suggests, to secure that the speeds of road users do not exceed the safe speed for a given type of environment. The purpose of this study was to make an evaluation of existing speed-securing measures on rural roads in Sweden to see how well they manage to limit the speed. A total of 34 unique locations have been filmed with drones with varying speed limits between 40 and 70 km/h. The analysis focused on the radius of both the individual vehicle trajectories and the radius of the roads themselves and how they relate to the speed choice of the drivers (including the 85th percentile speed). The result shows a moderate correlation between both types of radii and the speed choice of the drivers. In addition, the result also shows only a weak correlation between the driven radius and the radius of the roads themselves. Finally, the result also shows that only 17 locations manage to keep the 85th percentile speeds under the speed limit. Overall, the study suggests that the radius of the infrastructure is an important factor to lower the speed but the lack of a clear relationship between the driven radius and the radius of the road shows that more research is needed to properly understand why some locations work better than others.
DOI: 10.6084/m9.figshare.27996865
title: A study on lane-changing risk evolution of vehicle group based on potential field model in the freeway tunnel approach section

description: In the freeway tunnel approach section, lane-changing behaviors and transitions in the driving environment exacerbate traffic flow disruptions, increase driving risks, and lead to a higher accident rate. To this end, this study presents a method to explore the risk evolution process of lane-changing in these sections and evaluate its impact on traffic flow operations surrounding lane-changing vehicles. First, a driving risk potential field model based on the field theory, which consists of a vehicle kinetic potential field and a tunnel illumination potential field, is proposed to evaluate the driving risk. Furthermore, a “vehicle group” risk graph was constructed based on graph theory, incorporating both a node-coupling driving risk model and a topological potential entropy model. Finally, trajectory datasets were collected through naturalistic driving tests to analyze the evolution of lane-changing risk and the stability of the vehicle group. From the analysis of coupling driving risk evolution, we found that in the [100, 500) m, [500, 1000) m, and [1000, 1500) m freeway tunnel approach sections, the coupled driving risk of lane-changing vehicle (LCV) was higher than that of the other vehicles in the vehicle group. In different tunnel approach sections, LCVs that received the highest risk were from different vehicles in vehicle group. LCVs received the highest field strength from the risk potential fields of the lateral vehicle (LV), front lateral vehicle (FLV), and front vehicle (FV) in the [100, 500) m, [500, 1000) m, [1000, 1500) m tunnel approach sections, respectively. Based on the absolute value of the vehicle group topological potential entropy, we observed the resilience of the vehicle group system improved with increasing distance from the tunnel entrance. Traffic flow regained stability more quickly after lane-changing disturbances in sections farther from the tunnel entrance. This study highlights that the section closer to the freeway tunnel entrance significantly impact lane-changing risk, and it takes longer for the vehicle group to recover its stability after a lane-changing disturbance. The research results offer a theoretical and methodological foundation for enhancing traffic safety measures and developing microscopic driving behavior models for freeway tunnel approach sections.