TY - GEN
T1 - Monitoring of Spatio-Temporal Properties with Nonlinear SAT Solvers
AU - Matos Pedro, André de
AU - Silva, Tomás
AU - Sequeira, Tiago
AU - Lourenço, João
AU - Costa Seco, João
AU - Ferreira, Carla
N1 - Funding Information:
info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04516%2F2020/PT#
Acknowledgments. This work was partially supported by the European Regional Development Fund (ERDF) through the Competitiveness and Internationalization Operational Program (COMPETE 2020) of Portugal 2020 [Project STEROID with number 069989 (POCI-01-0247-FEDER-069989)].
Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2022
Y1 - 2022
N2 - The automotive industry is increasingly dependent on computing systems with variable levels of critical requirements. The verification and validation methods for these systems are now leveraging complex AI methods, for which the decision algorithms introduce non-determinism, especially in autonomous driving. This paper presents a runtime verification technique agnostic to the target system, which focuses on monitoring spatio-temporal properties that abstract the evolution of objects’ behavior in their spatial and temporal flow. First, a formalization of three known traffic rules (from the Vienna convention on road traffic) is presented, where a spatio-temporal logic fragment is used. Then, these logical expressions are translated to a monitoring model written in the first-order logic, where they will be processed by a non-linear satisfiability solver. Finally, the translation allows the solver to check the validity of the encoded properties according to an instance of a specific traffic scenario (a trace). The results obtained from our tool that automatically generates a monitor from a formula show that our approach is feasible for online monitoring in a real-world environment.
AB - The automotive industry is increasingly dependent on computing systems with variable levels of critical requirements. The verification and validation methods for these systems are now leveraging complex AI methods, for which the decision algorithms introduce non-determinism, especially in autonomous driving. This paper presents a runtime verification technique agnostic to the target system, which focuses on monitoring spatio-temporal properties that abstract the evolution of objects’ behavior in their spatial and temporal flow. First, a formalization of three known traffic rules (from the Vienna convention on road traffic) is presented, where a spatio-temporal logic fragment is used. Then, these logical expressions are translated to a monitoring model written in the first-order logic, where they will be processed by a non-linear satisfiability solver. Finally, the translation allows the solver to check the validity of the encoded properties according to an instance of a specific traffic scenario (a trace). The results obtained from our tool that automatically generates a monitor from a formula show that our approach is feasible for online monitoring in a real-world environment.
UR - https://www.scopus.com/pages/publications/85137994382
U2 - 10.1007/978-3-031-15008-1_11
DO - 10.1007/978-3-031-15008-1_11
M3 - Conference contribution
AN - SCOPUS:85137994382
SN - 978-3-031-15007-4
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 155
EP - 171
BT - Formal Methods for Industrial Critical Systems
A2 - Groote, Jan Friso
A2 - Huisman, Marieke
PB - Springer
CY - Cham
T2 - 27th International Conference on Formal Methods for Industrial Critical Systems, FMICS 2022
Y2 - 14 September 2022 through 15 September 2022
ER -