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Formal Verification of Collision Avoidance for Nonlinear Autonomous Vehicle Models


Publication Type:

Report - MRTC


Mälardalen Real-Time Research Centre, Mälardalen University




Autonomous vehicles are expected to be able to automatically avoid static and dynamic obstacles such as humans. However, most of the collision-avoidance functionality has not been formally verified, which is important for ensuring the safety of these systems. In this paper, we introduce the formal definitions of the vehicle's movement and trajectory based on hybrid transition systems. Since formally verifying hybrid systems is undecidable, we reduce the verification of nonlinear vehicle models to verification of discrete-time vehicle models and prove that the results of the latter imply the results of the former in this problem. Using this result, we propose a generic approach to formally verify autonomous vehicles with nonlinear behavior against reach-avoid requirements. Our approach provides a timed-automata model of vehicle behavior, and uses UPPAAL STRATEGO for verifying the model with user-programmed libraries of collision-avoidance algorithms. The experiments demonstrate the applicability of the approach, and its effectiveness in discovering bugs in a state-of-the-art version of a selected collision-avoidance algorithm, as well as proving the absence of bugs in the improved version of the algorithm.


author = {Rong Gu and Cristina Seceleanu and Eduard Paul Enoiu and Kristina Lundqvist},
title = {Formal Verification of Collision Avoidance for Nonlinear Autonomous Vehicle Models},
month = {April},
year = {2021},
publisher = {M{\"a}lardalen Real-Time Research Centre, M{\"a}lardalen University},
url = {}