On How to Not Prove Faulty Controllers Safe in Differential Dynamic Logic
Paper in proceeding, 2022

Cyber-physical systems are often safety-critical and their correctness is crucial, as in the case of automated driving. Using formal mathematical methods is one way to guarantee correctness. Though these methods have shown their usefulness, care must be taken as modeling errors might result in proving a faulty controller safe, which is potentially catastrophic in practice. This paper deals with two such modeling errors in differential dynamic logic. Differential dynamic logic is a formal specification and verification language for hybrid systems, which are mathematical models of cyber-physical systems. The main contribution is to prove conditions that when fulfilled, these two modeling errors cannot cause a faulty controller to be proven safe. The problems are illustrated with a real world example of a safety controller for automated driving, and it is shown that the formulated conditions have the intended effect both for a faulty and a correct controller. It is also shown how the formulated conditions aid in finding a loop invariant candidate to prove properties of hybrid systems with feedback loops. The results are proven using the interactive theorem prover KeYmaera X.

Theorem proving

Automated driving

Formal verification

Hybrid systems

Loop invariant

Author

Yuvaraj Selvaraj

Chalmers, Electrical Engineering, Systems and control

Zenseact AB

Jonas Krook

Zenseact AB

Chalmers, Electrical Engineering, Systems and control

Wolfgang Ahrendt

Chalmers, Computer Science and Engineering (Chalmers), Formal methods

Martin Fabian

Chalmers, Electrical Engineering, Systems and control

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

03029743 (ISSN) 16113349 (eISSN)

Vol. 13478 281-297
978-3-031-17244-1 (ISBN)

International Conference on Formal Engineering Methods, ICFEM 2022
Madrid, Spain,

Automatically Assessing Correctness of Autonomous Vehicles (Auto-CAV)

VINNOVA (2017-05519), 2018-03-01 -- 2021-12-31.

Subject Categories

Information Science

Control Engineering

Computer Science

Computer Systems

DOI

10.1007/978-3-031-17244-1_17

More information

Latest update

10/27/2023