Automated Synthesis of Certifiable Control Software for Autonomous Vehicles

Autonomous driving is a dominant technological theme of the 21st century, with vehicles from various car manufacturers equipped with different levels of autonomy.

However, the implementation of safe and reliable control software remains a critical challenge for car manufacturers before fully autonomous vehicles become a reality.

The current lack of reliability in autonomous vehicle software is mainly attributed to the absence of formal correctness. Design requirements are not expressed in a formal language, leading to ambiguity and false implementations.

Furthermore, human factors from engineers to developers increase the likelihood of errors, and testing scenarios are limited, leaving many edge cases untested.

Immature control software leading to accidents undermines public trust in autonomous vehicles and impedes further development.

We propose leveraging our ongoing ERC project AutoCPS research to create robust, reliable, and formally correct automotive control software.

CertiCar proposes a software development framework that automates control software generation and guarantees its robustness and reliability.

A reliable advanced collision avoidance system (ACAS) is a fundamental requirement for future autonomous vehicles, significantly reducing the number of accidents, injuries, and fatalities.

CertiCar's PoC project aims to provide a correct-by-design ACAS with guaranteed correctness, reducing testing time by several orders of magnitude for car companies, and represents an initial step toward a complete software stack for a certifiable autonomous car.