Multidimensional risk assessment for vehicle trajectories by using copulas

Fight against road unsafety is a French government priority. The policy conducted since 2002 allowed to obtain undeniable success. Despite this improvement, road accidents have very serious consequences on human level for road users. The proposed methods to reduce these accidents involve independence between criteria of accident risk. The objective of this study is to estimate the multidimensional risk of failure trajectory. It consists to investigate a new method of risk assessment in order to better characterize the dependence structure between the vehicle criteria for safety acceptance. This requires the use of simulation techniques such as copulas methods. This function connects the joint probability distribution to the marginal distribution. Thus, it contains all information on the dependence structure of models. However, the difficulty of multidimensional risk is to choose the copula which capture the better dependence between criteria. To select an adequate copula must be based on a statistical test. The khi2 test used in the framework of the adjustment of a parametric distribution to an empirical distribution is in this regard an interesting tool for the choice of copula. The experiments have shown the relevance and effectiveness of this method. The results will help to better assess the risk of failure trajectory for vehicles.

Data and Resources

Additional Info

Field Value
Source ICOSSAR
Author Koita, Abdourahmane, Daucher, Dimitri, Fogli, Michel
Maintainer CCSD
Last Updated May 9, 2026, 14:58 (UTC)
Created May 9, 2026, 14:58 (UTC)
Identifier hal-00865839
Language en
Rights https://about.hal.science/hal-authorisation-v1/
contributor Laboratoire Exploitation, Perception, Simulateurs et Simulations (IFSTTAR/COSYS/LEPSIS) ; Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-Communauté Université Paris-Est
creator Koita, Abdourahmane
date 2013-06-16T00:00:00
harvest_object_id c23ca857-adb0-40e0-9044-ee9010f48425
harvest_source_id 3374d638-d20b-4672-ba96-a23232d55657
harvest_source_title test moissonnage SELUNE
metadata_modified 2023-08-07T00:00:00
set_spec type:COMM