TY - GEN
T1 - Toward an Enhanced Risk Assessment Sensitivity for Autonomous Vehicles with the Safety Potential Field Approach
AU - Zuo, Dachuan
AU - Bian, Zilin
AU - Zuo, Fan
AU - Ozbay, Kaan
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - Ensuring safety encodes its most important position in autonomous vehicle (AV) technology, with a growing awareness on the role of risk assessment for advancing AV safety. Traditional risk assessment metrics often neglect crucial lateral interactions, struggle to reflect risk evolution, and find it challenging to capture comprehensive risks from multiple objects. Although recent literature mitigated these shortcomings through the safety potential field approach, their methods still exhibit lack in sensitivity to relative motions and inaccurate aggregation of risks from various objects. This paper intro-duces a novel real-time risk assessment metric for AVs that harnesses the instantaneous increment of vehicular potential energy within the safety potential field, namely instantaneous increment of potential energy (IIP). This metric enhances the sensitivity of risk assessment for AVs by capturing relative motions and buying more response time by capturing the progress of risk formation. The performance of IIP are validated by multiple simulation-based case studies and showed superiority over conventional time-to-collision (TTC) type of metrics in detecting lateral risks. The results underscore the potential of proposed metric to predict hazards and guide AV actions, enhancing safety in AV driving environment.
AB - Ensuring safety encodes its most important position in autonomous vehicle (AV) technology, with a growing awareness on the role of risk assessment for advancing AV safety. Traditional risk assessment metrics often neglect crucial lateral interactions, struggle to reflect risk evolution, and find it challenging to capture comprehensive risks from multiple objects. Although recent literature mitigated these shortcomings through the safety potential field approach, their methods still exhibit lack in sensitivity to relative motions and inaccurate aggregation of risks from various objects. This paper intro-duces a novel real-time risk assessment metric for AVs that harnesses the instantaneous increment of vehicular potential energy within the safety potential field, namely instantaneous increment of potential energy (IIP). This metric enhances the sensitivity of risk assessment for AVs by capturing relative motions and buying more response time by capturing the progress of risk formation. The performance of IIP are validated by multiple simulation-based case studies and showed superiority over conventional time-to-collision (TTC) type of metrics in detecting lateral risks. The results underscore the potential of proposed metric to predict hazards and guide AV actions, enhancing safety in AV driving environment.
KW - Autonomous vehicles
KW - Risk assessment
KW - Safety poten-tial field
UR - http://www.scopus.com/inward/record.url?scp=105001673889&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=105001673889&partnerID=8YFLogxK
U2 - 10.1109/ITSC58415.2024.10919717
DO - 10.1109/ITSC58415.2024.10919717
M3 - Conference contribution
AN - SCOPUS:105001673889
T3 - IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC
SP - 2889
EP - 2894
BT - 2024 IEEE 27th International Conference on Intelligent Transportation Systems, ITSC 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 27th IEEE International Conference on Intelligent Transportation Systems, ITSC 2024
Y2 - 24 September 2024 through 27 September 2024
ER -