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Hit-and-run crashes often have severe consequences for vulnerable road users. In light of governmental efforts to promote pedestrian-friendly urban environments, the significance of these crashes cannot be overstated. In this study, we assessed the factors that influence the injury severity of pedestrians involved in hit-and-run crashes in Ghana. Historical crash data (1469 observations) spanning from 2013 to 2020 was used in this study. An injury-severity model was developed using random parameters logit approach to assess what crash factors significantly affect the injury outcome of the crashes. It was observed that hit-and-run crashes that occur on dark and unlit roadways were more likely to result in fatal injuries. Also, female pedestrians were less likely to be killed in hit-and-run crashes. These findings provide the basis for developing and implementing appropriate countermeasures, such as punitive laws for drivers who leave the crash scene and protective laws for those who help their victims. [ABSTRACT FROM AUTHOR]

Work zones are crucial for maintaining and enhancing road infrastructure, but they also pose a significant risk to traffic safety. Between 2016 and 2020, work zone-related crashes in the United States increased by 13%, highlighting the pressing need for effective safety measures. This study examines the factors that influence work zone crashes, including traffic control devices, geometric configurations, traffic operations, and human factors. The study also investigates how these factors vary by work zone type, day of the week, and time of day. To explore these temporal and spatial impacts, the study utilized five years of fatal crash data from the Fatality Analysis Reporting System (FARS) and applied association rules mining. The findings demonstrate that rear-end crashes and collisions with other vehicles are the primary contributing factors. Although some common patterns emerged in the association rules, the study revealed temporal instability, highlighting the importance of developing work zone-specific safety countermeasures. These findings will inform the development of targeted safety interventions and ultimately reduce the risk of work zone crashes. [ABSTRACT FROM AUTHOR]

This study aims to discover hidden patterns and potential relationships in risk factors in freight truck crash data. Existing studies mainly used parametric models to analyze the causes of freight vehicle crashes. However, predetermined assumptions and underlying relationships between independent and dependent variables have been cited as its limitations. To overcome these limitations and provide a better understanding of factors that lead to truck crashes on the expressways, we applied the Association Rules Mining (ARM) technique, which is a nonparametric method. ARM quantifies the interrelationships between the antecedents and consequents of truck-involved crashes and provides researchers with the most influential set of factors that leads to crashes. We utilized a freight vehicle-involved crash data consisting of 19,038 crashes that occurred on the Korean expressways from 2008 to 2017 for this investigation. From the data, 90,951 association rules were generated through ARM employing the Apriori algorithm. The lift values estimated by the Apriori algorithm showed the strength of association between risk factors, and based on the estimated lift values, we identified key crash contributory factors that lead to truck-involved crashes at various segment types, under different weather conditions, considering the driver's age, crash type, driver's faults, vehicle size, and roadway geometry type. From the generated rules, we demonstrated that overspeeding with medium-weight trucks was highly associated with crashes during the rainy weather, whereas drowsy driving during the evening was correlated with crashes during fine weather. Segment-related crashes were mainly associated with driver's faults and roadway geometry. Our results present useful insights and suggestions that can be used by transport stakeholders, including policymakers and researchers, to create relevant policies that will help reduce freight truck crashes on the expressways., 1. Introduction The demand for freight transportation has been increasing concurrently with the growing population experienced globally [1]. In order to meet the needs of consumers, the number of trucks, [...]

Fatal crashes involving Powered Two-Wheelers (PTWs) are a major health concern in South Korea due to the increase in their usage in the logistics industry. Owing to the way, they are operated on the roadways, most riders end up in fatal crashes. Interestingly, little research exists regarding the impact of risk factors on fatal crashes involving at-fault PTW riders. This study employs a copula-based regression technique to simultaneously model the relationship between crash-risk factors and crash outcome metrics of fatal PTW rider-at-fault crashes, namely the number of crash casualties (casualty size) and the number of vehicles involved in a crash (crash size) at intersections and non-intersection segments. The proposed method was superior compared to the SEM-based bivariate regression approach, and the estimation results showed that there exists a positive relationship between both outcome variables. From the analysis, it was identified that while "other violations" comprising speeding and wrongful overtaking had varying effects on crash size outcomes at the intersection and non-intersection segments, variables such as daytime, winter, head-on collisions, and pedestrian involvement had positive impact on the crash consequence metrics irrespective of the crash location. Insights drawn from the study are used in recommending appropriate countermeasures for improving PTW safety. [ABSTRACT FROM AUTHOR]

Frontage roads are the supporting roadways that are along freeways and fully controlled principal arterial roadway networks in the U.S. These roads are designed in a way to provide access between the freeways, principal arterials, and surrounding business entities. For Texas, these roadways are the leading design resolution for providing access along rural freeways and principal arterial roadways. These roadways are generally two-ways for rural and less developed urban areas and are mostly one-way for urban and city-centered roadways. Although frontage roadways possess major safety concerns, the safety performance of these roadways has not been well studied. This study collected six years of frontage road crash data from Texas to determine the patterns of associated factors by applying a dimension reduction method known as cluster correspondence analysis (CCA). The results revealed four clusters for each of the two datasets based on crash injury types. For fatal and injury crashes, the major clusters are distraction-related crashes at signalized intersections, segment-related crashes at dark unlighted conditions, yield signed intersection locations and segments with no TCDs, and intersection crashes on undivided roadways. For the no injury crash dataset, the key clusters are segment crashes in dark conditions and rain, crashes at signalized intersections with both drivers going straight, segment crashes with both drivers going straight with marked lanes or no TCDs, and intersection-related collisions on undivided roadways. Based on the evaluation results, suitable safety countermeasures and policy initiatives to reduce frontage road crash frequencies can be singled out. [ABSTRACT FROM AUTHOR]