Predicting the safety impact of a speed limit increase using condition-based multivariate Poisson lognormal regression
| Autor: | Maria-Ioanna M. Imprialou, Mohammed A. Quddus, David Pitfield |
|---|---|
| Rok vydání: | 2015 |
| Předmět: |
050210 logistics & transportation
Multivariate statistics Speed limit 05 social sciences Geography Planning and Development Bayesian probability Transportation Regression analysis Regression Transport engineering 0502 economics and business Statistics Single vehicle 0501 psychology and cognitive sciences Limit (mathematics) Poisson lognormal human activities 050107 human factors Mathematics |
| Zdroj: | Transportation Planning and Technology. 39:3-23 |
| ISSN: | 1029-0354 0308-1060 |
| DOI: | 10.1080/03081060.2015.1108080 |
| Popis: | Speed limit changes are considered to lead to proportional changes in the number and severity of crashes. To predict the impact of a speed limit alteration, it is necessary to define a relationship between crashes and speed on a road network. This paper examines the relationship of crashes with speed, as well as with other traffic and geometric variables, on the UK motorways in order to estimate the impact of a potential speed limit increase from 70 to 80 mph on traffic safety. Full Bayesian multivariate Poisson lognormal regression models are applied to a data set aggregated using the condition-based approach for crashes by vehicle (i.e. single vehicle and multiple vehicle) and severity (i.e. fatal or serious and slight). The results show that single-vehicle crashes of all severities and fatal or serious injury crashes involving multiple vehicles increase at higher speed conditions and particularly when these are combined with lower volumes. Slight injury multiple-vehicle crashes are found not to... |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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