Abstract
We introduce a method for assessing the influence of
various road, weather and traffic conditions on traffic
accidents. The idea is to contrast the distribution of
conditions as seen by the driver involved in an accident
with their distribution as seen by an arbitrary driver.
The latter is considered as a variant of the notion of
Palm probability of a point process, and it is easy to
compute when road, weather and traffic measurement data
are available. The method includes straightforward
assessment of the statistical significance of the
findings. We then study a single large example case,
Ring-road I in Helsinki observed over five years, and
present a comprehensive analysis of the influence of
traffic, road and weather conditions on traffic
accidents. Our results are in line with existing
knowledge; for example, the traffic volume as such has
hardly any influence on accidents, whereas the afternoon
rush hours are considerably more risky than the morning
ones, and heavy rain and snowfall as well as reduced
visibility in general increase the accident risk
substantially. The notion of Palm probability offers a
transparent and uniform approach to such questions, and
the proposed approach can be applied as a semi-automatic
risk assessment tool prior to deeper analyses.
| Original language | English |
|---|---|
| Pages (from-to) | 48-65 |
| Journal | Analytic Methods in Accident Research |
| Volume | 12 |
| DOIs | |
| Publication status | Published - 2016 |
| MoE publication type | A1 Journal article-refereed |
Keywords
- Palm distribution
- Traffic accident risk
- Traffic condition
- Weather condition
- Statistical testing
