To improve the application range of decision‐making systems for connected automated
vehicles, this paper proposes a cooperative decision‐making approach for multiple driving …

To address the safety and efficiency issues of vehicles at multi-lane merging zones, a
cooperative decision-making framework is designed for connected automated vehicles …

Automated driving is essential for developing and deploying intelligent transportation
systems. However, unavoidable sensor noises or perception errors may cause an …

To address the coordination issue of connected automated vehicles (CAVs) at urban
scenarios, a game-theoretic decision-making framework is proposed that can advance …

Autonomous driving is one of the most important AI applications and has attracted extensive
interest in recent years. A large number of studies have successfully applied reinforcement …

This paper presents a hierarchical and game-theoretic decision-making strategy for
connected and automated vehicles (CAVs). A CAV can receive preview information using …

Despite rapid advances in vehicle intelligence and connectivity, there is still a significant
period in mixed traffic where connected, automated vehicles and human-driven vehicles …

In this paper, we proposed a decentralized cooperative lane-changing decision-making
framework for connected autonomous vehicles, which is composed of three modules, ie …

Safety is one of the major concerns in autonomous driving tasks, and enhancing the
collision avoidance ability of connected and autonomous vehicles (CAVs) is an effective way …

To improve the safety and efficiency of the intelligent transportation system, particularly in
complex urban scenarios, in this paper a game theoretic decision-making framework is …