The Palm distribution of traffic conditions and its application to accident risk assessment

Ilkka Norros, Pirkko Kuusela, Satu Innamaa, Eetu Pilli-Sihvola, Riikka Rajamäki

Research output: Contribution to journalArticleScientificpeer-review

8 Citations (Scopus)

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 languageEnglish
Pages (from-to)48-65
JournalAnalytic Methods in Accident Research
Volume12
DOIs
Publication statusPublished - 2016
MoE publication typeA1 Journal article-refereed

Fingerprint

accident risk
Risk assessment
risk assessment
Accidents
Highway accidents
traffic accident
road
traffic
accident
driver
traffic volume
statistical significance
road traffic
Snow
Visibility
Rain
knowledge

Keywords

  • Palm distribution
  • Traffic accident risk
  • Traffic condition
  • Weather condition
  • Statistical testing

Cite this

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title = "The Palm distribution of traffic conditions and its application to accident risk assessment",
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.",
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author = "Ilkka Norros and Pirkko Kuusela and Satu Innamaa and Eetu Pilli-Sihvola and Riikka Rajam{\"a}ki",
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The Palm distribution of traffic conditions and its application to accident risk assessment. / Norros, Ilkka; Kuusela, Pirkko; Innamaa, Satu; Pilli-Sihvola, Eetu; Rajamäki, Riikka.

In: Analytic Methods in Accident Research, Vol. 12, 2016, p. 48-65.

Research output: Contribution to journalArticleScientificpeer-review

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AU - Norros, Ilkka

AU - Kuusela, Pirkko

AU - Innamaa, Satu

AU - Pilli-Sihvola, Eetu

AU - Rajamäki, Riikka

N1 - Project code: 104704

PY - 2016

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AB - 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.

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