Traffic Accidents in Jordan

In Jordan, traffic accidents constitute a major health problem. They are considered the second leading cause of death. This paper investigated the characteristics of traffic accidents in Jordan and evaluated the safety impact of policy measures undertaken in 2008, including intensification of police enforcement and implementation of traffic law with stiff penalty levels. To accomplish these objectives, accidents’ data of 1998 through 2007 were obtained from Jordan Traffic Institute and other related sources. Results of analysis revealed that Jordan has experienced huge human and economic losses as well as social and emotional negative impacts. Children, young and elderly have been exposed to an elevated pedestrian accident risk. Young drivers of ages less than 25 years and elderly of ages over 60 years are over-involved in accidents. Carelessness and aggressive driving behavior were the major causes of traffic accidents. The results of analysis also indicated that motorization level can be used to explain variations in traffic accidents and fatalities. Furthermore, intensifying of traffic enforcement and implementing traffic law with stiff penalty levels were found to have a strong positive safety impact on accidents and fatalities. Finally, it is recommended to restructure and empower the Higher Council for Traffic Safety to be able to draw a comprehensive strategy with clear vision and rational safety policies to tackle the traffic accidents’ problem

Traffic Volume Forecasting for Rural Roads in Jordan

The accuracy of traffic forecasting is a point of considerable importance to the effective allocation of limited resources. Thus, reasonable and accurate forecasting methods should be developed to help engineers and planners make rational decisions and reduce probable associated risks. This study investigated the performance of three forecasting methods: aggregate regression, disaggregate trend and empirical Bayesian analysis. To accomplish this objective, traffic volumes for major rural roads in 1996 through 2004 were obtained from the Ministry of Public Works and Housing of Jordan. For each city or zone, cross-sectional data on socio-economic and demographic variables were collected. Multivariate regression analysis was carried out to develop mathematical relationships that could have practical applications. The results indicated that the products of populations-to-roadway length ratio, number of employees, fuel consumption, number of buildings and road type significantly influenced traffic interchange between cities or zones. For Jordan conditions, the linear model was recommended. Trend models, having exponential form, were also developed. Performance analysis indicated that aggregate regression and empirical Bayesian analysis provided comparable results. In contrast, the performance of trend method was considered to be poor. Finally, while these results are related to Jordan, they possibly apply elsewhere as well

The Duration Between Traffic Accidents in the Taxi Sector: An Empirical Inquiry

The taxi, as a supplier of urban passenger transport, is often sidelined in travel demand studies, yet its role in the overall transport task is far from marginal. Taxis are the most intensively used automobile transportation and consequently have a very high exposure rate in respect of potential accident. Very little empirical research has been undertaken into the risks associated with using a taxi. Drivers of taxis are usually assumed to be experienced drivers with a safety history appropriate for the responsibility of transporting the public. Yet this is not always the case. To provide some understanding of the exposure to risk which passengers place themselves in when hiring a taxi, we explore the safety record of drivers over time. Of particular interest is the frequency of accidents over a given time period, and in particular the elapsed time between a taxi drivers initial accident and subsequent accidents. To what extent is the duration between accidents a positive or negative function of experience, personal attributes, temporary impairment, fatigue etc? A set of proportional hazards models are developed to explain the time interval (duration) between traffic accidents of taxi drivers in Amman, Jordan. Three econometric models are developed to predict the duration between the date when a taxi driver begins to drive and the date when the first, second, and third accidents occur respectively. Estimation results show that driving-related capabilities, socioeconomic characteristics, and temporary impairments significantly influence the duration between traffic accidents. The duration to the first traffic accident is lower than the duration between the firs

Bayesian approach to the estimation of expected number of accidents

The primary objective of this research was to develop an empirical Bayesian approach to estimate the expected number of accidents and the accident rate at a group of sites as well as at individual site level. A methodology was also developed to evaluate safety impacts of highway projects. Rural traffic accident data from the state of Indiana were used in the study. The Bayesian models were investigated and they provided a legitimate estimate of the expected number of accidents specifically under steady state traffic volume conditions. Models were also developed to estimate the accident rates. The results of accident rate models indicated a good correspondence between predicted and observed values at the group of sites level. The Bayesian methodology to evaluate the safety impact of highway projects was illustrated through the examples of wedge and level and resurfacing projects