Traffic accident risk: measures

One could reasonably believe that complaining of chronic daytime somnolence is a major risk for traffic accidents. Surprisingly, studies on patients suffering from chronic daytime somnolence (9,10) failed to find a link between the risk of traffic accidents and sleepiness measured on a behavioral scale (i.e., Epworth Sleepiness Scale). This could be explained by the fact that subjective questionnaires do not correlate with objective measures of daytime vigilance (11). Another possible explanation could be that sleepiness is dangerous only when perceived during at risk activities. 

An attempt was made to explain what RHT says and what it does not. What it does say is that the essential outcome of road safety measures, that is, the accident rate per capita, ultimately depends on the amount of accident risk road users are willing to accept in exchange for their desire to satisfy needs other than safety. As was noted in Section 5.4, reduction of a jurisdiction s accident rate per kilometre driven over time is not accompanied by a reduction in the accident rate per capita. This does not mean that interventions that reduce the accident rate per unit distance driven are useless. On the contrary, such interventions allow drivers to cover greater distances against the same loss in terms of death, injury, and property damage. These interventions may, however, not be useful for the purpose of advancing public health in terms of the number of people being killed or injured in traffic. 

One very detailed analysis of pedestrian crash, injury, and fatality risk that considered the different exposure measures was conducted by Keall (1995). For his analysis he combined travel exposure data from the 1989- 1990 New Zealand Travel Survey with pedestrian accident data from the New Zealand national Traffic Accident Report files for the period 1988-1991. The travel survey data for children 5-9 years old were obtained from interviews with the parents or other adults in the same household. Their casualty data as a function of the pedestrian age is plotted in Figure 15-2. If we look first at the absolute numbers of pedestrians injured or killed as a function of age and gender we see the expected high numbers of young (5-19 years old) pedestrians. We also see that more males than females are injured or killed. 

This study investigates and compares the changes in speed distribution and estimated accident risk for three traffic safety measures, namely ... 

This theory is based on the assumption that the operator is able to perceive a risk level in the environment that is related to the actual risk level through a delayed feedback. The operator adapts his or her behaviour in such a way that there is a balance between the hazards that the operator is exposed to and what he or she can accept (target level of risk). It follows from this theory that measures to reduce hazards at the workplace will be followed by changed behaviour on the part of the operators such that their perceived level of risk remains the same. The only way to improve safety is to change the operators target risk level. The risk-homeostasis theory was primarily developed for situations where people voluntarily expose themselves to accident risks such as in traffic. We must expect, however, that employees at a workplace also to some extent control the risk that they are exposed to based on their own experiences and preferences. 

Table 28.1 Some common measures of the risk of traffic accidents...

In the previous Section, we used different measures of the risk of traffic accidents. Let us rehearse the definition of the risk of accidents from Section 17.2 and look closer into how it is applied in the field of traffic safety. We defined the risk of accidents as a combination of measures of the probability or frequency of accidents involving losses per unit of exposure to a specified activity, and the extent of the losses (consequences). In occupational safety, we use the number of man-hours as a measure of exposure. In calculating the risk of traffic accidents, we usually use other exposure measures. When we want to assess the effects of transportation accidents on the health of the general public, exposure is measured as the number of inhabitants at risk during a specified period. We are also concerned with the risk of accidents in relation to the transportation work carried out. Here we use, for example, the number of vehicle km as an exposure measure. Table 28.1 above summarises some common traffic-risk measures. 

The traffic-safety work has been organised into a number of result areas in order to make it more focused. SNRA has defined performance indicators for each area to follow up on progress. There is a known relationship between the changes within each area, as measured by the performance indicator and the risk of traffic accidents. Table 28.2 shows an overview of some of the performance measures and the goal for each for year 2000. 

There is no meaning to use the total number of fatalities or injuries to compare the safety problem in ASEAN countries, due to wide differences in population and motorisation in these countries. Measures of risk are essential in comparing different countries and studying the development of the road safety situation. Therefore, numbers of deaths have to be translated into measurable indicators that take road usage and exposure to accidents into account. The two general indicators of death rates relevant to our comparisons are traffic risk (fatalities per vehicles) and personal risk (fatalities per... 

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. 

In response to stakeholder concerns regarding the safety of maritime transportation, various approaches to ship collision risk have been proposed. Where the risk is seen as a measure of safety. Some studies concern probabilistic risk assessment and management. Such methods are aimed at probabilistically identifying areas of high ship collision risk e.g. using statistical methods (Friis-Hansen Simonsen 2002), traffic simulation (Goerlandt Kujala 2011) and combined accident statistics and ship domain analysis (Montewka et al. 2012). Another studies concern operational risk assessment, where ship collision risk is considered in real-time dynamic traffic situations onboard vessels or in Vessel Traffic Service (VTS) centers. Various methods for decision support in collision... 

Table 17.1 gives an overview of standard loss-based SHE performance indicators. In calcnlating the frequency of accidents, the size of the activity for which performance is assessed has to be considered. We must expect more accidents to occur in a large company than in a small one, even if the activities are similar. It is necessary to standardise the indicators in relation to the exposure to the risk of accidents. For occupational accidents, the most common exposure measure is the number of employee-hours. In traffic safety, for example, we use the number of vehicle kilometres or passenger kilometres as measures of exposure. By combining the frequency measures with the consequence measures, a measure of the risk is arrived at. 

The risk homeostatic approach implies that safety policy can increase traffic safety through insurance rates, traffic fines, driver education and other measures which influence the benefits and costs of safety as perceived by roadway users. For detail on such incentive systems see Gerald J. S. Wilde and Paul A. Murdoch. Incentive Systems for Accident-Free and Violation-Free Driving in the General Population. Ergonomics 25,10 (1982) 879-890. 

The financial externalities for mortality risks are estimated in Martin J. Bailey Reducing the Risks to Life Measurement of the Benefits (Washington, D.C. American Enterprise Institute, 1980). My calculation is based on figures found in U. S. Department of Transportation. National Highway Traffic Safety Administration. The Economic Cost to Society of Motor Vehicle Accidents. DOT HS 806 342, January 1983, pp. 1-4 and 1-5. 

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