Autonomous Navigation; Control Barrier Functions; Model Predictive Control; Pedestrian Behavior; Trust-aware Control
Résumé :
[en] A trust-aware safe control system for autonomous navigation in the presence of humans, specifically pedestrians, is presented. The system combines model predictive control (MPC) with control barrier functions (CBFs) and system-to-human trust (SHT) estimation to ensure safe and reliable navigation in human-populated environments. In the context of this article, we refer to SHT as the confidence score that a system has in an agent/pedestrian’s attentiveness. Pedestrian SHT values are computed based on features, extracted from camera sensor images, such as mutual eye contact, smartphone usage, and pose fluctuations and are integrated into the MPC controller’s CBF constraints, allowing the autonomous vehicle to make informed decisions considering pedestrian behavior. Simulations conducted in the CARLA driving simulator demonstrate the feasibility and effectiveness of the proposed system, showcasing more conservative behavior around inattentive pedestrians and vice versa. The results highlight the practicality of the system in real-world applications, providing a promising approach to enhance the safety and efficiency of autonomous navigation systems, especially self-driving vehicles.
Centre de recherche :
Interdisciplinary Centre for Security, Reliability and Trust (SnT) > ARG - Automation & Robotics
Disciplines :
Ingénierie, informatique & technologie: Multidisciplinaire, généralités & autres
Auteur, co-auteur :
EJAZ, Saad ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > Automation
Inoue, Masaki; Department of Applied Physics and Physico-Informatics, Keio University, Yokohama, Japan
Co-auteurs externes :
yes
Langue du document :
Anglais
Titre :
Trust-Aware Safe Control for Autonomous Navigation: Estimation of System-to-Human Trust for Trust-Adaptive Control Barrier Functions
Date de publication/diffusion :
29 octobre 2024
Titre du périodique :
IEEE Transactions on Control Systems Technology
ISSN :
1063-6536
Maison d'édition :
Institute of Electrical and Electronics Engineers (IEEE)
Titre particulier du numéro :
Special Issue on Intelligent Decision Making, Motion Planning and Control of Automated Vehicles in Interaction-driven Traffic Scenarios
This work was supported by Grant-in-Aid for Scientificc Research (B), No. 20H02173 JSPS. It was conducted as part of the JEMARO (Japan-Europe on Advanced Robotics) program, which is funded by the IUEP EU-Japan, MEXT, and the Erasmus+ program.
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