A proportional odds model of risk behaviors associated with recurrent road traffic crashes among young adults in Kuwait

Background The aims of this cross-sectional study were to i) assess one-year period prevalence of one, two, three or more road traffic crashes (RTCs) as an ordinal outcome and ii) identify the drivers’ characteristics associated with this ordinal outcome among young adult drivers with propensity to recurrent RTCs in Kuwait. Methods During December 2016, 1465 students, 17 years old or older from 15 colleges of Kuwait University participated in this cross-sectional study. A self-administered questionnaire was used for data collection. One-year period prevalence (95% confidence interval (CI)) of one, two, three or more RTCs was computed. Multivariable proportional odds model was used to identify the drivers’ attributes associated with the ordinal outcome. Results One-year period prevalence (%) of one, two and three or more RTCs respectively was 23.1 (95% CI: 21.2, 25.6), 10.9 (95% CI: 9.4, 12.6), and 4.6 (95% CI: 3.6, 5.9). Participants were significantly (p < 0.05) more likely to be in higher RTCs count category than their current or lower RCTs count, if they habitually violated speed limit (adjusted proportional odds ratio (pORadjusted) = 1.40; 95% Cl: 1.13, 1.75), ran through red lights (pORadjusted = 1.64; 95%CI: 1.30, 2.06), frequently (≥ 3) received multiple (> 3) speeding tickets (pORadjusted = 1.63; 95% CI: 1.12, 2.38), frequently (> 10 times) violated no-parking zone during the past year (pORadjusted = 1.64; 95% CI: 1.06, 2.54) or being a patient with epilepsy (pORadjusted = 4.37; 95% CI: 1.63, 11.70). Conclusion High one-year period prevalence of one, two and three or more RTCs was recorded. Targeted education based on identified drivers’ attributes and stern enforcement of traffic laws may reduce the recurrent RTCs incidence in this and other similar populations in the region.

Investigating the Impact of Connected and Automated Vehicles on Signalized and Unsignalized Intersections Safety in Mixed Traffic

Road traffic crashes are a major safety problem, with one of the leading factors in crashes being human error. Automated and connected vehicles (CAVs) that are equipped with Advanced Driver Assistance Systems (ADAS) are expected to reduce human error. In this paper, the Simulation of Urban MObility (SUMO) traffic simulator is used to investigate how CAVs impact road safety. In order to define the longitudinal behavior of Human Drive Vehicles (HDVs) and CAVs, car-following models, including the Krauss, the Intelligent Driver Model (IDM), and Cooperative Adaptive Cruise Control (CACC) car-following models were used to simulate CAVs. Surrogate safety measures were utilized to analyze CAVs’ safety impact using time-to-collision. Two case studies were evaluated: a signalized grid network that included nine intersections, and a second network consisting of an unsignalized intersection. The results demonstrate that CAVs could potentially reduce the number of conflicts based on each of the car following model simulations and the two case studies. A secondary finding of the research identified additional safety benefits of vehicles equipped with collision avoidance control, through the reduction in rear-end conflicts observed for the CACC car-following model.

Fatality risk and issues of inequity among vulnerable road users in South Africa

Background Contextual effects from the physical and social environment contribute to inequitable protection for a large proportion of road users, especially in low- and middle-income countries like South Africa where distorted urban planning and socio-spatial disparities from the apartheid era prevail. Objectives This paper examines the differentiated risk of road traffic crashes and injuries to vulnerable road users in South Africa, including pedestrians, females and users of some modes of public transport, in relation to characteristics of the crashes that proxy a range of contextual influences such as rurality and socio-economic deprivation. Methods The study is based on a descriptive analysis of 33 659 fatal crashes that occurred in South Africa over a three-year period from 2016–2018. Measures of simple proportion, population-based fatality rate, “impact factor” and crash severity are compared between disaggregated groups using Chi-Square analysis, with the Cramer’s V statistic used to assess effect size. Results and significance Key findings show a higher pedestrian risk in relation to public transport vehicles and area-level influences such as the nature of roads or extent of urbanity; higher passenger risk in relation to public transport vehicles and rurality; and higher risk for female road users in relation to public transport vehicles. The findings have implications for prioritising a range of deprivation-related structural effects. In addition, we present a “User-System-Context” conceptual framework that allows for a holistic approach to addressing vulnerability in the transport system. The findings provide an important avenue for addressing the persistently large burden of road traffic crashes and injuries in the country.

Mental health and behavioural factors involved in road traffic crashes by young adults: analysis of the Raine Study

BackgroundRoad traffic crashes (RTC) are a leading cause of mortality and morbidity in young people. Severe mental health and behavioural conditions increase the likelihood of RTC, as do a range of driving-risk activities.MethodWe used data from the Raine Study, a prebirth cohort from Perth, Australia, to assess the relationship between measures of common mental health or behavioural conditions (Child Behavior Checklist Internalising and Externalising scores) at age 17 and subsequent RTC by 27 years, controlling for substance use and driving-risk activities.ResultsBy 27 years of age, of 937 participants, 386 (41.2%) reported zero crashes and 551 (58.8%) reported ≥1 crashes. In the baseline Poisson model, increased Externalising scores (eg, aggression and delinquency) were associated with increased RTC (incidence rate ratio (IRR)=1.02, 95% CI 1.01 to 1.02): increased Internalising scores (eg, anxiety and depression) were associated with fewer RTC (IRR=0.99, 95% CI 0.98 to 1.00). In the fully adjusted model, the mental health measures were not significant (Externalising IRR=1.01, 95% CI 0.99 to 1.02: Internalising IRR=0.99, 95% CI 0.99 to 1.00). Risky driver activities, such as falling asleep while driving (IRR=1.34), more frequent use of a hands-free telephone (IRR=1.35) and more frequent hostility towards other drivers (IRR=1.30) increased the rate of RTC.ConclusionMeasures of mental health scores at age 17 were not predictive of subsequent RTC, after adjusting for measures of driving-risk activities. We need to better understand the determinants of externalising and risky driving behaviours if we are to address the increased risk of RTC.

Injury Metrics for Assessing the Risk of Acute Subdural Hematoma in Traumatic Events

Worldwide, the ocurrence of acute subdural hematomas (ASDHs) in road traffic crashes is a major public health problem. ASDHs are usually produced by loss of structural integrity of one of the cerebral bridging veins (CBVs) linking the parasagittal sinus to the brain. Therefore, to assess the risk of ASDH it is important to know the mechanical conditions to which the CBVs are subjected during a potentially traumatic event (such as a traffic accident or a fall from height). Recently, new studies on CBVs have been published allowing much more accurate prediction of the likelihood of mechanical failure of CBVs. These new data can be used to propose new damage metrics, which make more accurate predictions about the probability of occurrence of ASDH in road crashes. This would allow a better assessement of the effects of passive safety countermeasures and, consequently, to improve vehicle restraint systems. Currently, some widely used damage metrics are based on partially obsolete data and measurements of the mechanical behavior of CBVs that have not been confirmed by subsequent studies. This paper proposes a revision of some existing metrics and constructs a new metric based on more accurate recent data on the mechanical failure of human CBVs.

Study on the Impact of “Gerayo Amahoro Policy” on Road Traffic Accidents Reduction in Rwanda

The global status report on road safety declared that the number of annual road traffic deaths has reached 1.35 million. In Rwanda, considering the raising number of vehicles in line with the economy growth and the above 48.90/000 ratio of deaths per registered vehicles; the lives of people are therefore increasingly exposed to road traffic crashes. This study therefore aims to utilize statistical methods for assessing the impact of Gerayo Amahoro policy on Road Traffic Accidents reduction in Rwanda and propose counter measures that could help the decision makers in minimizing the losses caused by Road Traffic Accidents. secondary data related to road traffic accidents have been collected by using questionnaire from Rwanda National Police with the study period from 2016 up to 2020 inclusive. Analysis was done by using graphics and chi-square methods in excel and SPSS software. The results indicated that GERAYO AMAHORO policy plays the greatest role in reduction of RTAs in Rwanda due to the number of RTAs happened before the implementation of GERAYO AMAHORO which was high as compared to the total number of RTAs after implementation of GERAYO AMAHORO policy. This research conclude that negligence, over speed, bad maneuver and over drunk are mostly causes and responsible for the occurrence of RTAs in Rwanda; indicated that Vehicle types mostly related to RTAs were moto-cycles, cars and 4 wheel vehicles and the mostly victims related to RTAs were moto-cyclists, passengers and pedestrians.

OPTIMISING ROAD LIGHTING TO REDUCE ROAD TRAFFIC CRASHES

Pedestrians and motorcyclists are vulnerable road users, being over represented in road traffic collisions (RTCs). One assumed benefit of road lighting is a reduction in RTCs after dark by countering the impairment to the visual detection of hazards that occur after dark. One way to optimise the use of road lighting is to light only those sections of road where light level, and hence visibility, is an important factor. The current study used change in ambient light level on RTCs to investigate those situations where improved vision is likely to have significant impact, and therefore the situations where road lighting is of better cost-benefit effectiveness. For both motorcyclist and pedestrian RTCs there was a significant increase in overall RTC risk in darkness compared to daylight, indicating that there may be an overall benefit of road lighting. While darkness was a particular detriment at junctions for motorcyclists and on high-speed roads for pedestrians, road lighting may not be effective mitigation in either case and therefore alternative ways of increasing conspicuity should be considered.

Impact of night travel ban on road traffic crashes and fatalities in Zambia: an interrupted time series analysis

BackgroundThe burden of road traffic crashes (RTCs) and road traffic fatalities (RTFs) has been increasing in low-income and middle-income countries (LMICs). Most RTCs and RTFs happen at night. Although few countries, including Zambia, have implemented night travel bans, there is no evidence on the extent to which such policies may reduce crashes and fatalities.MethodsWe exploit the quasi-experimental set up afforded by the banning of night travel of public service vehicles in Zambia in 2016 and interrupted time series analysis to assess whether the ban had an impact on both levels and trends in RTCs and RTFs. We use annual administrative data for the period 2006—2020, with 10 pre-intervention and 4 post-intervention data points. In an alternative specification, we restrict the analysis to the period 2012—2020 so that the number of data points are the same pre-interventions and post-interventions. We also carry out robustness checks to rule out other possible explanation of the results including COVID-19.ResultsThe night travel ban was associated with a reduction in the level of RTCs by 4131.3 (annual average RTCs before the policy=17 668) and a reduction in the annual trend in RTCs by 2485.5. These effects were significant at below 1%, and they amount to an overall reduction in RTCs by 24%. The policy was also associated with a 57.5% reduction in RTFs. In absolute terms, the trend in RTFs reduced by 477.5 (Annual average RTFs before the policy=1124.7), which is significant at below 1% level. Our results were broadly unchanged in alternative specifications.ConclusionWe conclude that a night travel ban may be an effective way of reducing the burden of RTCs and RTFs in Zambia and other LMICs. However, complementary policies are needed to achieve more gains.