Automatically Learning Formal Models from Autonomous Driving Software

Author:

Selvaraj YuvarajORCID,Farooqui AshfaqORCID,Panahandeh Ghazaleh,Ahrendt WolfgangORCID,Fabian MartinORCID

Abstract

The correctness of autonomous driving software is of utmost importance, as incorrect behavior may have catastrophic consequences. Formal model-based engineering techniques can help guarantee correctness and thereby allow the safe deployment of autonomous vehicles. However, challenges exist for widespread industrial adoption of formal methods. One of these challenges is the model construction problem. Manual construction of formal models is time-consuming, error-prone, and intractable for large systems. Automating model construction would be a big step towards widespread industrial adoption of formal methods for system development, re-engineering, and reverse engineering. This article applies active learning techniques to obtain formal models of an existing (under development) autonomous driving software module implemented in MATLAB. This demonstrates the feasibility of automated learning for automotive industrial use. Additionally, practical challenges in applying automata learning, and possible directions for integrating automata learning into the automotive software development workflow, are discussed.

Funder

VINNOVA

Knut and Alice Wallenberg Foundation

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing,Control and Systems Engineering

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Automaton Model Updating Based on the L* Algorithm;Proceedings of the 2023 7th International Conference on Computing and Data Analysis;2023-09-15

2. Hazard Analysis of Collaborative Automation Systems: A Two-layer Approach based on Supervisory Control and Simulation;2023 IEEE International Conference on Robotics and Automation (ICRA);2023-05-29

3. Feasible, Robust and Reliable Automation and Control for Autonomous Systems;Electronics;2022-07-07

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