This paper suggests that the influence of a number of important risk factors on road accidents can be described in terms of a few highly general statistical regularities that determine the shape of the relationship between the risk factors and accident occurrence. The statistical regularities are referred to as "laws of accident causation". The following "laws" are proposed: The universal law of learning, which states that the ability to detect and control traffic hazards increases uniformly as the amount of travel increases. This law implies that accident rate per unit of exposure will decline as the amount of exposure increases. The law of rare events, which states that the more rarely a certain risk factor is encountered the larger is its effect on accident rate. This law implies that a risk factor encountered on, for example 5% of all trips, will be associated with a greater increase in accident rate than an otherwise identical risk factor encountered on 50% of all trips .The law of complexity, which states that the more units of information per unit of time a road user must attend to, the higher becomes the probability that an error will made. This law implies that accident rate will increase the more elements of information the traffic environment contains. The law of cognitive capacity, which states that the more cognitive capacity approaches its limits, the higher the accident rate. This law implies that impairments affecting mental functions will have a greater effect on accident rate than impairments affecting physical functioning only. Instances of all these laws, as well as a discussion of to how the laws can be tested empirically, are given. It is hoped that proposing a few basic mechanisms that can summarise the impact of a number of risk factors will stimulate research that may lead to a more general theory of accident causation. (A) "Reprinted with permission from Elsevier".
Samenvatting