The objective of this research is to present the state of the art of the safety assurance of
Artificial Intelligence (AI)-based systems and guidelines on future correlated work. For this …

This paper presents the first survey of vehicle dynamics modeling methods for autonomous
racing. Previous surveys have covered dynamics models for standard autonomous vehicles …

Traditional road testing of autonomous vehicles faces significant limitations, including long
testing cycles, high costs, and substantial risks. Consequently, autonomous driving …

Connected and automated vehicles will characterize the future of the mobility, featured by
Smart Roads and Internet of Things technologies. Vehicles will behave as mobile nodes of a …

Scenario‐based test methods are employed to assess the safety and performance of
autonomous vehicles. The analytic hierarchy process (AHP) method is a common …

Unsignalized intersection is one typical interactive driving scenarios that are challenging for
automated vehicles (AV). For safe, efficient and user-acceptable performances, the …

This study introduces a multilayer perceptron (MLP) error compensation method for real-time
camera orientation estimation, leveraging a single vanishing point and road lane lines within …

Autonomous vehicle (AV) requires millions of miles on road to test the reliability of safety
systems. It is also difficult to test the AV for critical scenarios which are rare but will endanger …

This study develops a methodology that estimates the lateral velocity of vehicles by
integrating an artificial neural network (ANN) with physics for optimal feature selection. In …

Machine learning (ML) has become a popular technique for various automation tasks in the
era of Industry 4.0, such as the analysis and synthesis of visual data such as images and …