TY - GEN
T1 - PerceMon
T2 - 21st International Conference on Runtime Verification, RV 2021
AU - Balakrishnan, Anand
AU - Deshmukh, Jyotirmoy
AU - Hoxha, Bardh
AU - Yamaguchi, Tomoya
AU - Fainekos, Georgios
N1 - Funding Information:
Acknowledgment. This work was partially supported by the National Science Foundation under grant no. CNS-2039087 and grant no. CNS-2038666, and the tool was developed with support from Toyota Research Institute North America.
Publisher Copyright:
© 2021, Springer Nature Switzerland AG.
PY - 2021
Y1 - 2021
N2 - Perception algorithms in autonomous vehicles are vital for the vehicle to understand the semantics of its surroundings, including detection and tracking of objects in the environment. The outputs of these algorithms are in turn used for decision-making in safety-critical scenarios like collision avoidance, and automated emergency braking. Thus, it is crucial to monitor such perception systems at runtime. However, due to the high-level, complex representations of the outputs of perception systems, it is a challenge to test and verify these systems, especially at runtime. In this paper, we present a runtime monitoring tool, PerceMon that can monitor arbitrary specifications in Timed Quality Temporal Logic (TQTL) and its extensions with spatial operators. We integrate the tool with the CARLA autonomous vehicle simulation environment and the ROS middleware platform while monitoring properties on state-of-the-art object detection and tracking algorithms.
AB - Perception algorithms in autonomous vehicles are vital for the vehicle to understand the semantics of its surroundings, including detection and tracking of objects in the environment. The outputs of these algorithms are in turn used for decision-making in safety-critical scenarios like collision avoidance, and automated emergency braking. Thus, it is crucial to monitor such perception systems at runtime. However, due to the high-level, complex representations of the outputs of perception systems, it is a challenge to test and verify these systems, especially at runtime. In this paper, we present a runtime monitoring tool, PerceMon that can monitor arbitrary specifications in Timed Quality Temporal Logic (TQTL) and its extensions with spatial operators. We integrate the tool with the CARLA autonomous vehicle simulation environment and the ROS middleware platform while monitoring properties on state-of-the-art object detection and tracking algorithms.
KW - Autonomous driving
KW - Perception monitoring
KW - Temporal logic
UR - http://www.scopus.com/inward/record.url?scp=85117525096&partnerID=8YFLogxK
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U2 - 10.1007/978-3-030-88494-9_18
DO - 10.1007/978-3-030-88494-9_18
M3 - Conference contribution
AN - SCOPUS:85117525096
SN - 9783030884932
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 297
EP - 308
BT - Runtime Verification - 21st International Conference, RV 2021, Proceedings
A2 - Feng, Lu
A2 - Fisman, Dana
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 11 October 2021 through 14 October 2021
ER -