Fatalities Traffic Fatality Rate

Silvak, M., (1983). Society s aggression level as a predictor of traffic fatality rate. Journal of Safety Research 14, pp. 93-99. 

An American study published in 2002 reported that car-occupant seatbelt usage, as determined by roadside surveys, had risen from a low of 10% (in 1985 in Indiana) to a high of 87% (in 1996 in California), but did not find this to have had the effect of reducing the traffic fatality rate per head of population across as many as 14 years of data (Derrig et al., 2002). 

Jamroz K. (2012) The impact of road network structure and mobility on the national traffic fatality rate. EWGT 2012. 15th meeting of the EURO Working Group on Transportation. Procedia—Social and Behavioral Sciences 54 (2012) pp. 1370-1377. www. elsevier.com/locate/procedia. 

FATALR j—traffic fatality rate in an i-th region in j-th year... 

Peltzman s article has been criticized on a number of counts, primarily statistical but it did stimulate follow-up investigations. Dr. John Adams of University College, London, UK, for example, compared traffic fatality rates between countries with and without safety-belt use laws. His annual comparisons (from 1970 to 1978) showed dramatic reductions in fatal vehicle crash rates after countries introduced seat-belt use laws. Taken alone this data would lend strong support to seat-belt legislation. But the drop in fatality rates was even greater in countries without safety-belt use laws (Adams, 1985b). Apparently, the large-scale impact of increased use of vehicle safety belts has not been nearly as beneficial as expected from laboratory crash tests. Risk compensation has been proposed to explain this discrepancy. 

Sam Peltzman s methodological approach differs from the technological approach in that he focuses on human behavior especially driver choice. He begins with an individual benefit-cost framework to traffic safety and combines with it findings from other safety studies to construct counterfactual estimates of traffic fatality rates, hypothetical rates which would have occurred without a national traffic safety policy. We will examine his study in some detail because most of the studies are similar m crucial aspects and hence we can examine other studies more quickly. Peltzman s study is pivotal in that it was one of the first comprehensive evaluative studies. It reintroduced human behavior into traffic safety thinking. 

IMPACT OF VEHICLE SAFETY STANDARDS ON TRAFFIC FATALITY RATES AND LIVES SAVED... 

Table 3.3 shows the estimated deaths (from road crashes) per 100,000 population experienced in the various WHO regions of the world in 2008. We can readily see that, on average, low-income and middle-income countries have around twice the road traffic fatality rates of high-income countries. 

Answer The automobile death rate is about lE-7/passenger mile. If 25,000 people evacuate 20 miles, this is 5E5 passenger miles, hence, the risk is 5E5 IE-7 = 0.05 deaths. The radiation exposure is 2.5E4 5E-4 48 = 600 person-rem. Using information from problem 4, the estimated deaths from radiation is 600 lE-4 = 0.06. About the same. The risk from radiation may be over estimated because the radiation level was measured close to the plant on the other hand, the traffic fatality estimate may be high because of police presence and slow driving. 

In this study only industrial and traffic accident risks are discussed in Chongqing City and Ningbo City, China, which is typical developing and developed area, respectively. Industrial accident risk is described by yearly industrial accident death toll (lAD) and yearly fatality rate per 105 workers (FRW) and traffic accident risk is composed of yearly traffic accident death toll (TAD) and yearly mortality rate per 104 vehicles (MRV). 

IV. Risk and post-crash injury outcome Different studies have shown that fatality rates are correlated with the level of medical facilities available in the country expressed in terms of population per physician and population per hospital bed, see (Jacobs Fouracre, 1977) and (Mekky, 1985). A review of a European study, in (WHO, 2004), showed that about half of deaths from road accidents occurred at the spot of the accident or on the way to the hospital. Noland (2003) concludes that medical care has led to reductions in traffic-related fatalities in developed countries over time (1970-1996). The variables used are infant mortality rates, physicians per capita, and average acute care days in hospital. 

Nevertheless, some other studies have tried to explain why the curve of development (fatality rates) declines downwards as been noted in many countries and shown in Smeed s formula. The studies have analysed the factors and measures that influence the development of the curve of road safety. A review of these studies is reported by (Elvik Vaa, 2004) and (Hakim, 1991). Besides, Minter (1987) and Oppe (1991b) showed that Smeed s law is a result of a national learning process over time. The development in society at the national level is the result from the developments at the local level. In other words, the individuals (road users) can learn by experience in traffic where they improve their driving skills and knowledge, while the whole society can learn by better national policy and action plans. The Figure shown here illustrates these factors on the development curve of road safety. 

This model can also be used for estimating or predicting the data from the equation, i.e., by predicting what will happen to traffic fatalities if the same trends of motorisation continue with the same rates. We will leave this work for further analysis in future work. Besides, better curves could be obtained here if the analyses in the ASEAN countries had been divided into two categories of motorisation, one tine devoted for high-motorised ASEAN countries for each of (Brunei, Malaysia, Singapore and Thailand) and one tine for lower motorised countries for each (Vietnam, Indonesia, Cambodia, the Philippines, Myamnar and Laos). In tike maimer, we leave this work for future work. 

The first chosen dimension is the level of traffic risk in a country, which deals with the fatalities rates. The fatality rate per vehicle is currently used, while fatality rate per vehicle-km or per person-km or per type of road user (pedestrians, cyclists, motorcyclists and drivers) are all other indicators of this dimension and they can be used on the long term of RSDI. 

The indicators included in RSDI measure road safety development in terms of direct (output or ends) and indhect (means or input). The direct indicators are derived measures e.g. fatalities rates (traffic risk and personal risk) and they are considered as good measures for explaining national road safety development. The indirect indicators are individual means in the way they can describe the development in a particular relevant theme to road safety. Many international indices include both terms in the same index. For example, the Composite Health Index includes infant mortality rates as an ou ut (dhect) indicator of health index. 

Nearly all attempts to examine human factors found larger behaviour influences. Most of the accidents resulted from the violation of traffic laws. In one study carried out in Indiana State in USA presented in (Oppe, 1993), the frequencies of cause factors were calculated. The results have shown that in 70.7% of accidents the causes were human, 12,4% environmental and 4.5% vehicles. Furthermore, the measure of Traffic Risk is widely accepted in international comparisons and it deals with the fatalities rates per vehicles, per vehicles-km or per person-km. 

The World Health Organizalion statistics for 2008 show that there were nearly 4 million unintentional injury deaths worldwide. The average unintentional fatality rate among all age groups was 59 per 100,000 population. Road traffic accidents were the leading unintentional fatality cause for all age groups under 70. 

The same way of looking at risk can be seen in everyday life. In a typical large American city, around 500 people die each year in traffic accidents. Although many efforts are made to reduce this fatality rate, the fact remains that this loss of life is perceived as a necessary component of modem life hence, there is little outrage on the part of the public. Yet, if an airplane carrying 500 people crashed at that same city s airport every year, there would be an outcry. The fatality rate is the same in each case, i.e., 500 deaths per city per year. The difference between the two risks is a perception rooted in feelings and values. 

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