We introduce a counting process to model the random occurrence in time of car traffic accidents, taking into account some aspects of the self-excitation typical of this phenomenon. By combining methods from probability and differential equations, we study this stochastic process in terms of its statistical moments and large-time trend. Moreover, we derive analytically the probability density functions of the times of occurrence of traffic accidents and of the time elapsing between two consecutive accidents. Finally, we demonstrate the suitability of our modeling approach by means of numerical simulations, which also address a comparison with real data of weekly trends of traffic accidents.
Probabilistic modeling of car traffic accidents / Goettlich, Simone; Schillinger, Thomas; Tosin, Andrea. - In: SIAM JOURNAL ON APPLIED MATHEMATICS. - ISSN 1095-712X. - STAMPA. - 85:3(2025), pp. 1099-1120. [10.1137/24M1698262]
Probabilistic modeling of car traffic accidents
Tosin, Andrea
2025
Abstract
We introduce a counting process to model the random occurrence in time of car traffic accidents, taking into account some aspects of the self-excitation typical of this phenomenon. By combining methods from probability and differential equations, we study this stochastic process in terms of its statistical moments and large-time trend. Moreover, we derive analytically the probability density functions of the times of occurrence of traffic accidents and of the time elapsing between two consecutive accidents. Finally, we demonstrate the suitability of our modeling approach by means of numerical simulations, which also address a comparison with real data of weekly trends of traffic accidents.File | Dimensione | Formato | |
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https://hdl.handle.net/11583/3000213