Work

Data-inspired modeling of accidents in traffic flow networks

Year: 2025
Type: article
Abstract: We consider hyperbolic partial differential equations (PDEs) for a dynamic description of the traffic behavior in road networks. These equations are coupled to a Hawkes process that models traffic accidents taking into account their self-excitation property which means that accidents are more likely in areas in which another accident just occurred. We discuss how both model components interact and influence each other. A data analysis reveals the self-excitation property of accidents and determines further parameters. Numerical simulations using risk measures underline and conclude the discussion of traffic accident effects in our model.
Language: English
Open Access status: diamond
OpenAlex ID: W4409245701
FWCI:
Cites: 39
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Related to: 10