Investigating factors affecting bus/minibus accident severity in a developing country for different subgroup datasets characterised by time, pavement, and light conditions

Stability of factors influencing walking-along-the-road pedestrian injury severity outcomes under different lighting conditions: A random parameters logit approach with heterogeneity in means and out-of-sample predictions

Pedestrians walking along the road's edge are more exposed and vulnerable than those on designated crosswalks. Often, they remain oblivious to the imminent perils of potential collisions with vehicles, making crashes involving these pedestrians relatively unique compared to others. While previous research has recognized that the surrounding lighting conditions influence traffic crashes, the effect of different lighting conditions on walking-along-the-road pedestrian injury severity outcomes remains unexplored. This study examines the variations in the impact of risk factors on walking-along-the-road pedestrian-involved crash injury severity across various lighting conditions. Preliminary stability tests on the walking-along-the-road pedestrian-involved crash data obtained from Ghana revealed that the effect of most risk factors on injury severity outcomes is likely to differ under each lighting condition, warranting the estimation of separate models for each lighting condition. Thus, the data were grouped based on the lighting conditions, and different models were estimated employing the random parameter logit model with heterogeneity in the means approach to capture different levels of unobserved heterogeneity in the crash data. From the results, heavy vehicles, shoulder presence, and aged drivers were found to cause fatal pedestrian walking-along-the-road severity outcomes during daylight conditions, indicators for male pedestrians and speeding were identified to have stronger associations with fatalities on roads with no light at night, and crashes occurring on Tuesdays and Wednesdays were likely to be severe on lit roads at night. From the marginal effect estimates, although some explanatory variables showed consistent effects across various lighting conditions in pedestrian walking-along-the-road crashes, such as pedestrians aged < 25 years and between 25 and 44 years exhibited significant variations in their impact across different lighting conditions, supporting the finding that the effect of risk factors are unstable. Further, the out-of-sample simulations underscored the shifts in factor effects between different lighting conditions, highlighting that enhancing visibility could play a pivotal role in significantly reducing fatalities associated with pedestrians walking along the road. Targeted engineering, education, and enforcement countermeasures are proposed from the interesting insights drawn to improve pedestrian safety locally and internationally.

Factors affecting motorcycle crash casualty severity at signalized and non-signalized intersections in Ghana: Insights from a data mining and binary logit regression approach

Despite the countless benefits derived from motorcycle usage, it has become a significant public health concern, particularly in developing countries, due to the plateauing number of fatal/serious injuries associated with them. Although it has been well documented that the frequency and fatality rates of intersection-related motorcycle crashes are high, little research efforts have been made to explore the contributory factors influencing motorcycle-involved crashes at these locations. Interestingly, no study has investigated the latent patterns and chains of factors that simultaneously contribute to the injury severity sustained by motorcycle crash casualties at intersections under different traffic control conditions in developing countries. Since motorcycles are mostly used as taxis in developing countries, it is imperative to consider the injury severity sustained by all crash casualties in the motorcycle safety analysis. This study bridges the research gap by employing a plausible data mining tool to explore hidden rules associated with motorcycle crash casualty injury severity outcomes at both signalized and non-signalized intersections in Ghana's most densely populated region, Accra, using three-year crash data spanning 2016-2018. Besides, a binary logit regression model was also employed to explore the impact of crash factors on casualty severity outcomes using the same dataset. The results from both analysis techniques were consistent; however, the data mining technique provided chains of factors which provided additional insights into the groups of factors that collectively influence the casualty injury severity outcomes. From the rule discovery results, while full license status, daytime/daylight, and shoulder presence increased the risk of fatal injuries at signalized intersections, factors such as inattentiveness, good road surface, nighttime, shoulder absence, and young rider were highly likely to increase casualty fatalities at non-signalized intersections. By controlling all or some of these risk factors, the level of injury severity on the roadways could be reduced. Based on the findings, we provide enforcement, education, and engineering-based recommendations to help improve motorcycle safety.

Driving Performance Evaluation of Shuttle Buses: A Case Study of Hong Kong-Zhuhai-Macau Bridge

The risky behaviours of bus drivers are of great concern to public health and environmental sustainability, especially for the buses operated between cities. With this in mind, the present study examined the distribution of risky behaviours among bus drivers, and the contributing factors to risky performance. To achieve this, 1648 records of GPS trajectory data and 8281 records of advance warning message data from Hong Kong–Zhuhai–Macau Bridge shuttle buses were obtained. The temporal and spatial distribution of risky behaviours was analysed. A random parameters negative binomial model was developed to further investigate the relationship between speed-related factors and risky behaviours. The results indicated that the warning of safety distance, lane departure, forward collision, and distraction were more likely to occur on weekdays. The period between 14 and 16 o’clock obtained the highest frequency of safety distance and lane departure warnings. Regarding the model estimation results, indicators reflecting average speed, acceleration, and number of trips per day showed a statistically significant impact on safety distance and lane departure warnings. Also, the acceleration of bus drivers showed a mixed impact on lane departure warnings. Corresponding implications were discussed according to the findings to reduce the frequency of risky behaviours in shuttle bus operations.