Analyzing injury severity of three-wheeler motorized rickshaws: A correlated random parameters approach with heterogeneity in means.

Traffic crashes involving three-wheeler motorized rickshaw (3-WMR) are alarming public health and socioeconomic concerns in developing countries. While most of the earlier studies have dealt with safety analysis of four- and two-wheelers, there is a noticeable gap in understanding the safety dynamics, especially the risk factors affecting the crashes involving 3-WMR. The present study aims to address this gap by exploring potential risk factors influencing 3-WMR crashes, utilizing a correlated random parameters multinomial logit model with heterogeneity in means (CRPMNLMHM). This modeling framework advances the classic random parameters model by capturing associations among random parameters, providing a more comprehensive understanding of crash risks associated with 3-WMR. The empirical analysis draws on three years of traffic crash records (2017-2019) maintained by RESCUE 1122 in Rawalpindi city, Pakistan. A comparative assessment between the modeling frameworks demonstrated that CRPMNLMHM outperformed its counterparts. Model assessment for heterogeneity in the means identifies two significant variables, i.e., young age and nighttime, which yield statistically significant random parameters. In addition, the model's results suggest that fatal and severe injury outcomes in 3-WMR crashes are affected by several attributes related to temporal characteristics (weekend, nighttime, and off-peak indicators), driver profiles (young, older aged, and speeding), posted speed limits (>70 kmph), weather conditions (raining), and crash characteristics (collision with pedestrians, trucks, or 3-WMR overturning). The present study's findings offer invaluable insights, emphasizing the significance of considering for unobserved heterogeneity in variables contributing to the injury severity of 3-WMR crashes. Moreover, in light of the findings, a set of policy implications are suggested, which will guide safety practitioners to develop more effective countermeasures to address safety issues associated with 3-WMRs.

Examination of factors associated with the temporal stability assessment of crash severity by using generalised linear model-A case study.

Road crashes are a major public safety concern in Pakistan. Prior studies in Pakistan investigated the impact of different factors on road crashes but did not consider the temporal stability of crash data. This means that the recommendations based on these studies are not fully effective, as the impact of certain factors may change over time. To address this gap in the literature, this study aims to identify the factors contributing to crash severity in road crashes and examine how their impact varies over time. In this comprehensive study, we utilized Generalised Linear Model (GLM) on the crash data between the years 2013 to 2017, encompassing a total sample of 802 road crashes occurred on the N-5 road section in Pakistan, a 429-kilometer stretch connecting two big cities of Pakistan, i.e., Peshawar and Lahore. The purpose of the GLM was to quantify the temporal stability of the factors contributing crash severity in each year from 2013 to 2017. Within this dataset, 60% (n = 471) were fatal crashes, while the remaining 40% (n = 321) were non-fatal. The results revealed that the factors including the day of the week, the location of the crashes, weather conditions, causes of the crashes, and the types of vehicles involved, exhibited the temporal instability over time. In summary, our study provides in-depth insights aimed at reducing crash severity and potentially aiding in the development of effective crash mitigation policies in Pakistan and other nations having similar road safety problems. This research holds great promise in exploring the dynamic safety implications of emerging transportation technologies, particularly in the context of the widespread adoption of connected and autonomous vehicles.

Exploring factors affecting the injury severity of freeway tunnel crashes: A random parameters approach with heterogeneity in means and variances.

Generally, freeway tunnels are built to overcome the complex driving environments in mountainous terrains. However, crashes in these tunnels can be more severe than those on the open road sections due to their closed driving environment. Despite the higher crash severity, very few studies have attempted to investigate the severity of injuries in freeway tunnel crashes. Also, the existing studies on the injury severity analysis of tunnels did not fully consider the unobserved heterogeneity and its interactive effects. To address these issues, the present study first collected a comprehensive dataset containing five-year of police-reported tunnel crashes from Hunan province, China. A random parameters model with heterogeneity in means and variances was then developed to explore the influence of different variables related to the environment, drivers, crashes, vehicles, and tunnels. The study observed that the presence of curves and speeding indicators produce random parameters with heterogeneity in means and variances for freeway tunnels, which is influenced by the young drivers and outside exit zone variables. Also, the results reveal that factors, including weekdays, daytime, speeding, fatigue driving, rear-end collisions, collisions with fixtures, large passenger vehicles, and downgrades increase, while rain reduces the probability of severe injury outcomes in freeway tunnel crashes. More importantly, considering the unique tunnel driving environment, the summer, young drivers, novice drivers, presence of curves, and different tunnel sections (access, entrance, and outside exit zones) also significantly affect the risk of severe injury outcomes. Finally, the study's findings could be used as a basis for developing plans and technologies to minimize the severity of crash injuries in freeway tunnels.

What Factors Would Make Single-Vehicle Motorcycle Crashes Fatal? Empirical Evidence from Pakistan.

The existing research on motorcycle safety has shown that single-vehicle motorcycle crashes (SVMC) account for a higher fatality rate than other types of crashes. Also, motorcycle safety has become one of the critical traffic safety issues in many developing countries, such as Pakistan, due to the growing number of motorcycles and lack of sufficient relevant infrastructure. However, the available literature on SVMC and motorcycle safety in developing countries is limited. Therefore, the present study attempted to investigate the factors that contribute to the injury severity of SVMC in a developing country, Pakistan. For this purpose, a random parameter logit model with heterogeneity in means and variances is developed using two years of data extracted from the road traffic injury research project in Karachi city, Pakistan. The study's findings show that the presence of pillion passengers and young motorcyclists indicators result in random parameters with heterogeneity in their means and variances. The study's results also reveal that the summer, morning time, weekends, older motorcyclists, collisions with fixed objects, speeding, and overtaking are positively, while younger motorcyclists and the presence of pillion passengers are negatively associated with fatal crashes. More importantly, in the particular Pakistan's context, female pillion passenger clothes trapped in the wheel, riding under the influence, intersections, U-turns, and collisions due to loss of control are also found to significantly influence the injury severity of SVMC. Based on these research findings, multiple appropriate countermeasures are recommended to enhance motorcycle safety in Pakistan and other developing countries with similar problems.

Understanding drivers' awareness, habits and intentions inside road tunnels for effective safety policies.

Tunnels have a unique driving environment; thus, a small incident in a tunnel may result in severe consequences and a high probability of secondary crashes. Fortunately, studies have found that adopting safe driving behavior in a tunnel minimizes the severe outcomes of an incident. Therefore, implementing driver-oriented safety policies and conducting public awareness campaigns that emphasize safe behavior when driving through tunnels are essential. However, before devising policies and campaigns on the right issues, it is necessary to understand drivers' current level of knowledge regarding tunnel safety, their habits, behavioral intentions, and psychological condition while driving through tunnels. To achieve this objective, a sample of 841 responses was collected from China using a questionnaire survey consisting of fifty-two items. The results showed that several gaps exist in drivers' knowledge regarding tunnel safety and equipment. Drivers often adopt inappropriate habits and behaviors while driving through tunnels. Also, the tunnel environment has a significant influence on the psychological condition of the drivers. Moreover, drivers' demographic characteristics significantly affect their knowledge, reported habits and behavioral intentions, and psychological condition. The authorities and safety analysts could employ the suggestions highlighted in the present study for improving tunnel safety.

Impacts of COVID-19 on individuals' mobility behavior in Pakistan based on self-reported responses.

The COVID-19 pandemic has been extremely disturbing mobility behavior due to travel restrictions and perceived COVID-19 threats. Recently, researchers from developed countries have shown interest in quantifying the impacts of the COVID-19 on individuals' mobility; however, similar research themes in lower income developing countries like Pakistan have not been sufficiently explored. Therefore, the objectives of the study are; 1) to explore the changes in self-reported individual's mobility behavior-trip frequencies by mode and by purpose in three COVID-19 severity periods; 2) to quantify the effects of respondents' personal (i.e., age, gender, education, and living place), and perceived details (i.e., safety perceptions, the COVID-19 threat perceptions) on the change in mobility behavior in the COVID-19 severity change; 3) to analyze the willingness to use public transportation in the post-pandemic period. METHODS: A web-based questionnaire survey was conducted from September 2020 to November 2020, resulting in 565 responses. Descriptive analysis, random parameter bivariate probit modeling, and structural equation modeling are adopted to achieve the objectives. RESULTS: The results reflect the change in individuals' mobility behavior in three severity periods of COVID-19, including before outbreak, during the most serious period, and after the most serious period. A substantial reduction in individuals' mobility was observed during the most serious period, which is recovering back to normal. The results also indicate the relationship of individuals' personal and perceived characteristics with the change in mobility in COVID-19 severity changes from before-to-serious and from the serious-to-after most serious period. CONCLUSION: The COVID-19 pandemic has been affecting individuals' mobility behavior in Pakistan. The study's findings provide insightful information for the transportation agencies to better prepare for sustainable transportation management in the post-pandemic era.

Revisiting freeway single tunnel crash characteristics analysis: A six-zone analytic approach.

Considerable studies have been conducted to investigate the tunnels' traffic safety. However, the entrance and exit parts of a tunnel are mostly considered symmetrical in previous studies, and the different lengths (long, medium, and short) of tunnels have not been separately studied. This study aims to investigate the characteristics of traffic crashes in freeway single tunnels by separately considering the entrance and exit of the tunnel as well as the different lengths of tunnels. A six-zone approach is proposed, and the data from 156 single tunnels in Hunan province, China, are applied for safety analysis. The crash rate, crash type, and contributing crash factors are compared between the conventional four-zone approach and the proposed method, and the three types of tunnels with different lengths are also compared for in-depth analysis. Results show that the proposed six-zone method provides a better understanding of the tunnels crash characteristics. The most crash-prone zones for long, medium, and short tunnels are the mid-zone, the entrance zone, and the access zone, respectively. Furthermore, at the tunnel entrance, drivers usually fail to maintain safe distance, which results in the high proportion of rear-end crashes, while at the tunnel exit, they do speeding and improper lane change that increases the risk of sideswipe, rollover, and collision with fixed objects. The study also discusses the crash occurrence mechanism for different types of tunnels. Findings of this study shed some light on the engineering and policy implications for improving traffic safety of the freeway tunnels.