About this Engineering article
Estimating the accident potential of an Ontario driver by E. Hauer; B.N. Persaud; A. Smiley; D. Duncan is a Engineering article available to read on EtoBox.
To run a "demerit point" program, one uses routinely available information about drivers to identify those who are most likely to have an accident in the near future. On the basis of a four-year record for a large sample of Ontario drivers, we have examined several tools for the identification of such drivers and investigated how they perform. Each driver is thought to have an expected number of accidents, m. In a group of drivers with common traits (such as age, gender, record of convictions and accidents) the ms have a mean E(m) and a variance VAR(m). Estimates of E(m) and VAR(m) for all combinations of traits can be obtained within the framework of a multivariate statistical model. The same estimates can then be used to judge how well a model identifies drivers who have a large m. In such a multivariate model it is important to use data about previous accidents and convictions. However, the accuracy with which the m of a driver can be estimated is not improved much by distinguishing between offence type or between accidents as being "at fault" or "not at fault". Without much loss in estimation accuracy, one may attach a weight 1 to a conviction and 2 to an accident. Model perfor
It is typically read by researchers, students, and practitioners in Engineering.
- Author
- E. Hauer; B.N. Persaud; A. Smiley; D. Duncan
- Publisher
- Elsevier Science; Elsevier ; Elsevier Ltd.; Elsevier BV (ISSN 0001-4575)
- Published
- 1991
- Language
- EN
- Field
- Engineering (Physical Sciences)