We provide a review of recent work on formal methods for autonomous driving. Formal
methods have been traditionally used to specify and verify the behavior of computer …

In the era of technological transformation, mobility and transportation systems are becoming
more intelligent and greener. Thanks to powerful technologies and tools, electric and …

Automated Driving Systems (ADSs) have seen rapid progress in recent years. To ensure the
safety and reliability of these systems, extensive testings are being conducted before their …

Abstract Context Machine Learning (ML) has been at the heart of many innovations over the
past years. However, including it in so-called “safety-critical” systems such as automotive or …

The increasing complexity and connectivity of automotive systems have raised concerns
about their vulnerability to security breaches. As a result, the integration of formal methods …

Artificial Intelligence (AI) can enable the development of next-generation autonomous safety-
critical systems in which Machine Learning (ML) algorithms learn optimized and safe …

This paper surveys the state-of-the-art contributions supporting the validation of virtual
testing toolchains for Automated Driving System (ADS) verification. The work builds upon the …

Autonomous vehicles (AVs) have emerged as a promising technology for enhancing road
safety and mobility. However, designing AVs involves various critical aspects, such as …

We perform a systematic literature review on testing, validation, and verification of robotic
and autonomous systems (RAS). The scope of this review covers peer-reviewed research …

Images captured through the glass often consist of undesirable specular reflections. These
reflections detected in front of the glass remarkably reduce the quality and visibility of the …