Crash testing of experimental safety vehicles. Volume II - Renault Basic Research Vehicle. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

A comparison of road accidents in developing countries with special reference to Jamaica

This research was originally undertaken to aid the Jamaican government and the World Bank in making funding decisions relative to improvement of road systems and traffic control in Jamaica. An investigation of the frequency and causes of road accidents and an evaluation of their impact on the Jamaican economy were carried out, and a model system which might be applied was developed. It is believed that the importance of road accident economic and manpower losses to the survival of developing countries, such as Jamaica, cannot be overemphasized. It is suggested that the World Bank, in cooperation with national governments, has a role to play in alleviating this serious problem. Data was collected from such organizations as the Jamaica Ministry of Construction, Police Department, the World Bank, and the World Health Organization. A variety of methodologies were utilized to organize this data in useful and understandable forms. The most important conclusion of this research is that solvable problems in road systems and in traffic control result in the unnecessary loss of useful citizens, in both developed and developing countries. However, a lack of information and understanding regarding the impact of high rates of road accident death and injury on the national economy and stability of a country results in an apparent lack of concern. Having little internal expertise in the field of road accident prevention, developing countries usually hire consultants to help them address this problem. In the case of Jamaica, this practice has resulted in distrust and hard feelings between the Jamaican authorities and major organizations involved in the field. Jamaican officials have found confusing the recommendations of most experts contracted to study traffic safety. The attempts of foreign consultants to utilize a technological approach (the use of coding systems and computers), methods which do not appear cost-effective for Jamaica, have resulted in the expenditure of limited funds for studies which offer no feasible approach to the problem. This funding limitation, which hampers research and road improvement, could be alleviated by such organizations as the World Bank. The causes of high accident rates are many, it was found. Formulation of a plan to address this serious problem must take into account the current failure to appreciate the impact of a high level of road accidents on national economy and stability, inability to find a feasible approach to the problem, and inadequate funding. Such a plan is discussed in detail in the main text of this research.

Investigation of the causes of serious injury and fatal crashes: An analysis using econometric models

The rate of fatal crashes in Florida has remained significantly higher than the national average for the last several years. The 2003 statistics from the National Highway Traffic Safety Administration (NHTSA), the latest available, show a fatality rate in Florida of 1.71 per 100 million vehicle-miles traveled compared to the national average of 1.48 per 100 million vehicle-miles traveled. The objective of this research is to better understand the driver, environmental, and roadway factors that affect the probability of injury severity in Florida. ^ In this research, the ordered logit model was used to develop six injury severity models; single-vehicle and two-vehicle crashes on urban freeways and urban principal arterials and two-vehicle crashes at urban signalized and unsignalized intersections. The data used in this research included all crashes that occurred on the state highway system for the period from 2001 to 2003 in the Southeast Florida region, which includes the Miami-Dade, Broward and Palm Beach Counties.^ The results of the analysis indicate that the age group and gender of the driver at fault were significant factors of injury severity risk across all models. The greatest risk of severe injury was observed for the age groups 55 to 65 and 66 and older. A positive association between injury severity and the race of the driver at fault was also found. Driver at fault of Hispanic origin was associated with a higher risk of severe injury for both freeway models and for the two-vehicle crash model on arterial roads. A higher risk of more severe injury crash involvement was also found when an African-American was the at fault driver on two-vehicle crashes on freeways. In addition, the arterial class was also found to be positively associated with a higher risk of severe crashes. Six-lane divided arterials exhibited the highest injury severity risk of all arterial classes. The lowest severe injury risk was found for one way roads. Alcohol involvement by the driver at fault was also found to be a significant risk of severe injury for the single-vehicle crash model on freeways. ^

Effects of roadway geometric features on run-off road crashes on the Florida State Highway System

Run-off-road (ROR) crashes have increasingly become a serious concern for transportation officials in the State of Florida. These types of crashes have increased proportionally in recent years statewide and have been the focus of the Florida Department of Transportation. The goal of this research was to develop statistical models that can be used to investigate the possible causal relationships between roadway geometric features and ROR crashes on Florida's rural and urban principal arterials. ^ In this research, Zero-Inflated Poisson (ZIP) and Zero-Inflated Negative Binomial (ZINB) Regression models were used to better model the excessive number of roadway segments with no ROR crashes. Since Florida covers a diverse area and since there are sixty-seven counties, it was divided into four geographical regions to minimize possible unobserved heterogeneity. Three years of crash data (2000–2002) encompassing those for principal arterials on the Florida State Highway System were used. Several statistical models based on the ZIP and ZINB regression methods were fitted to predict the expected number of ROR crashes on urban and rural roads for each region. Each region was further divided into urban and rural areas, resulting in a total of eight crash models. A best-fit predictive model was identified for each of these eight models in terms of AIC values. The ZINB regression was found to be appropriate for seven of the eight models and the ZIP regression was found to be more appropriate for the remaining model. To achieve model convergence, some explanatory variables that were not statistically significant were included. Therefore, strong conclusions cannot be derived from some of these models. ^ Given the complex nature of crashes, recommendations for additional research are made. The interaction of weather and human condition would be quite valuable in discerning additional causal relationships for these types of crashes. Additionally, roadside data should be considered and incorporated into future research of ROR crashes. ^

Lower limb and associated injuries in frontal-impact road traffic collisions.

Objectives: To study the relationship between severity of injury of the lower limb and severity of injury of the head, thoracic, and abdominal regions in frontal-impact road traffic collisions. Methods: Consecutive hospitalised trauma patients who were involved in a frontal road traffic collision were prospectively studied over 18 months. Patients with at least one Abbreviated Injury Scale (AIS) ≥3 or AIS 2 injuries within two AIS body regions were included. Patients were divided into two groups depending on the severity of injury to the head, chest or abdomen. Low severity group had an AIS < 2 and high severity group had an AIS ≥ 2. Backward likelihood logistic regression models were used to define significant factors affecting the severity of head, chest or abdominal injuries. Results: Eighty-five patients were studied. The backward likelihood logistic regression model defining independent factors affecting severity of head injuries was highly significant (p=0.01, nagelkerke r square = 0.1) severity of lower limb injuries was the only significant factor (p=0.013) having a negative correlation with head injury (Odds ratio of 0.64 (95% CI: 0.45-0.91). Conclusion: Occupants who sustain a greater severity of injury to the lower limb in a frontal-impact collision are likely to be spared from a greater severity of head injury.