Temporal Instability of Factors Affecting Injury Severity in Helmet-Wearing and Non-Helmet-Wearing Motorcycle Crashes: A Random Parameter Approach with Heterogeneity in Means and Variances

Not wearing a helmet, not properly strapping the helmet on, or wearing a substandard helmet increases the risk of fatalities and injuries in motorcycle crashes. This research examines the differences in motorcycle crash injury severity considering crashes involving the compliance with and defiance of helmet use by motorcycle riders and highlights the temporal variation in their impact. Three-year (2017–2019) motorcycle crash data were collected from RESCUE 1122, a provincial emergency response service for Rawalpindi, Pakistan. The available crash data include crash-specific information, vehicle, driver, spatial and temporal characteristics, roadway features, and traffic volume, which influence the motorcyclist’s injury severity. A random parameters logit model with heterogeneity in means and variances was evaluated to predict critical contributory factors in helmet-wearing and non-helmet-wearing motorcyclist crashes. Model estimates suggest significant variations in the impact of explanatory variables on motorcyclists’ injury severity in the case of compliance with and defiance of helmet use. For helmet-wearing motorcyclists, key factors significantly associated with increasingly severe injury and fatal injuries include young riders (below 20 years of age), female pillion riders, collisions with another motorcycle, large trucks, passenger car, drivers aged 50 years and above, and drivers being distracted while driving. In contrast, for non-helmet-wearing motorcyclists, the significant factors responsible for severe injuries and fatalities were distracted driving, the collision of two motorcycles, crashes at U-turns, weekday crashes, and drivers above 50 years of age. The impact of parameters that predict motorcyclist injury severity was found to vary dramatically over time, exhibiting statistically significant temporal instability. The results of this study can serve as potential motorcycle safety guidelines for all relevant stakeholders to improve the state of motorcycle safety in the country

Assessment of Significant Factors Affecting Frequent Lane-Changing Related to Road Safety: An Integrated Approach of the AHP–BWM Model

Frequent lane changes cause serious traffic safety concerns for road users. The detection and categorization of significant factors affecting frequent lane changing could help to reduce frequent lane-changing risk. The main objective of this research study is to assess and prioritize the significant factors and sub-factors affecting frequent lane changing designed in a three-level hierarchical structure. As a multi-criteria decision-making methodology (MCDM), this study utilizes the analytic hierarchy process (AHP) combined with the best–worst method (BWM) to compare and quantify the specified factors. To illustrate the applicability of the proposed model, a real-life decision-making problem is considered, prioritizing the most significant factors affecting lane changing based on the driver’s responses on a designated questionnaire survey. The proposed model observed fewer pairwise comparisons (PCs) with more consistent and reliable results than the conventional AHP. For level 1 of the three-level hierarchical structure, the AHP–BWM model results show “traffic characteristics” (0.5148) as the most significant factor affecting frequent lane changing, followed by “human” (0.2134), as second-ranked factor. For level 2, “traffic volume” (0.1771) was observed as the most significant factor, followed by “speed” (0.1521). For level 3, the model results show “average speed” (0.0783) as first-rank factor, followed by the factor “rural” (0.0764), as compared to other specified factors. The proposed integrated approach could help decision-makers to focus on highlighted significant factors affecting frequent lane-changing to improve road safety

A Fuzzy-Logic Approach Based on Driver Decision-Making Behavior Modeling and Simulation

The present study proposes a decision-making model based on different models of driver behavior, aiming to ensure integration between road safety and crash reduction based on an examination of speed limitations under weather conditions. The present study investigated differences in road safety attitude, driver behavior, and weather conditions I-69 in Flint, Genesee County, Michigan, using the fuzzy logic approach. A questionnaire-based survey was conducted among a sample of Singaporean (n = 100) professional drivers. Safety level was assessed in relation to speed limits to determine whether the proposed speed limit contributed to a risky or safe situation. The experimental results show that the speed limits investigated on different roads/in different weather were based on the participants’ responses. The participants could increase or keep their current speed limit or reduce their speed limit a little or significantly. The study results were used to determine the speed limits needed on different roads/in different weather to reduce the number of crashes and to implement safe driving conditions based on the weather. Changing the speed limit from 80 mph to 70 mph reduced the number of crashes occurring under wet road conditions. According to the results of the fuzzy logic study algorithm, a driver’s emotions can predict outputs. For this study, the fuzzy logic algorithm evaluated drivers’ emotions according to the relation between the weather/road condition and the speed limit. The fuzzy logic would contribute to assessing a powerful feature of human control. The fuzzy logic algorithm can explain smooth relationships between the input and output. The input–output relationship estimated by fuzzy logic was used to understand differences in drivers’ feelings in varying road/weather conditions at different speed limits

Substance abuse at early age as a potential risk factor for driving under the influence of substance in Jeddah, Saudi Arabia: A cross-sectional study

<p><b>Objective:</b> Worldwide, trauma is a major health problem, and road traffic accidents (RTAs) are the primary cause of death among young men in Saudi Arabia. The aim of our study was to estimate the extent of driving under the influence of an abused substance in Saudi Arabia and to explore the associated factors.</p> <p><b>Methods:</b> This is a cross-sectional survey conducted between May and September 2016 at Al-Amal Hospital in Jeddah, Saudi Arabia, a referral center for addiction. We included all patients who were admitted for additional education and rehabilitation and had no psychotic symptoms. We used a standardized and pretested questionnaire to collect data regarding sociodemographic and socioeconomic characteristics, history of and current substance abuse, driving under the influence of an abused substance, injuries, imprisonment, and fatalities under the influence of an abused substance. Whenever possible, we compared self-reported data with medical records and resolved any conflict by discussion with the patient.</p> <p><b>Results:</b> A total of 101 out of 112 invited patients participated in our study (90.2%). The mean age of the participants was 33.28 years (SD = 9.46 years). Of the total, 93.1% (<i>n</i> = 94) drove under the influence of an abused substance. Amphetamines and alcohol were the first substance abused (56.4% [<i>n</i> = 57] and 25.7% [<i>n</i> = 26] of patients, respectively). As currently abused substances, amphetamines and cannabis were reported in 38.6% (<i>n</i> = 39) and 24.8% (<i>n</i> = 25) of participants, respectively. The mean age at the time of the first substance abuse was 18.76 years (SD = 4.99 years). In the univariate regression (odds ratio [OR] = 0.86; 95% confidence interval [CI], 0.75–0.99; <i>P</i> = .046) but not the multivariate regression (OR =0.87; 95% CI, 0.75–1.00; <i>P</i> = .056), a younger age at the time of the first substance abuse was associated with a higher probability of driving under the influence of an abused substance.</p> <p><b>Conclusions:</b> Our study showed that among individuals hospitalized due to substance abuse problems, driving under the influence of drugs and alcohol was common. Preventive measures to reduce driving under the influence should be introduced in addition to specialized hospitals. Further research is required to investigate the factors associated with driving under the influence of abused substances in Saudi Arabia.</p