A Risk-Based Decision-Making Process for Autonomous Trains Using POMDP: Case of the Anti-Collision Function - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue IEEE Access Année : 2024

A Risk-Based Decision-Making Process for Autonomous Trains Using POMDP: Case of the Anti-Collision Function

Résumé

As the railway domain progresses towards autonomy, maintaining safety at levels comparable to human-operated systems is a crucial challenge. Autonomous trains require advanced systems capable of real-time risk assessment and decision-making, a task traditionally managed by human situational awareness. This paper introduces a novel risk-based decision-making approach for autonomous trains, using Partially Observable Markov Decision Processes (POMDPs) for continuous monitoring and evaluation of environmental collision risks. By consistently maintaining an acceptable risk level through ongoing risk estimation (in terms of occurrence probability and severity degree), the approach supports the decision-making capabilities of the autonomous driving system in autonomous trains, enabling safe and informed decisions despite the uncertainties in the train’s operational state and environmental conditions. The approach’s relevance and effectiveness are illustrated through its application in an anti-collision function for autonomous trains.
Fichier principal
Vignette du fichier
A_Risk-Based_Decision-Making_Process_for_Autonomous_Trains_Using_POMDP_Case_of_the_Anti-Collision_Function.pdf (9.82 Mo) Télécharger le fichier
Origine : Fichiers éditeurs autorisés sur une archive ouverte

Dates et versions

hal-04402491 , version 1 (04-04-2024)

Identifiants

Citer

Mohammed Chelouati, Abderraouf Boussif, Julie Beugin, El-Miloudi El-Koursi. A Risk-Based Decision-Making Process for Autonomous Trains Using POMDP: Case of the Anti-Collision Function. IEEE Access, 2024, 12, pp.5630-5647. ⟨10.1109/ACCESS.2023.3347500⟩. ⟨hal-04402491⟩
32 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More