Stochastic cusp catastrophe models with traffic and weather data for crash severity analysis on urban arterials
Athanasios Theofilatos
George Yannis
Eleni Vlahogianni
John Golias
2134/9874772.v1
https://repository.lboro.ac.uk/articles/conference_contribution/Stochastic_cusp_catastrophe_models_with_traffic_and_weather_data_for_crash_severity_analysis_on_urban_arterials/9874772
<p>The investigation of crash severity with freeway traffic and weather
data has recently received significant attention by researchers. This paper extends
previous research by proposing nonlinear models for modeling crash injury
severity enhanced with traffic and weather data collected from urban arterials
in Athens, Greece. Cusp catastrophe models are applied and compared with
traditional statistical models. The results of crash severity models support
the potential applicability of the cusp catastrophe theory to road safety, at
least when crash severity is expressed as the number of severely and fatally
injured by total number of persons involved in a crash. Variations in speed,
average flow upstream of the location of interest, crash type and wind speed,
were found to have a potential effect on the system dynamics. However, findings
do not always confirm the strong presence of nonlinearity. When crash severity
is expressed as the number of injured persons by the total number of vehicles
involved in a crash, linear models could also be used to describe the underlying
phenomenon. </p><br>
2019-09-19 12:55:42
Uncategorised value
Crash
Injury severity
Cusp catastrophe
Macroscopic traffic data
Weather information
Urban arterials