Complex, dynamic, and interactive environment brings huge challenges to autonomous
driving technologies. Because of the strong interactions between different traffic participants …

In this paper, a human-like driving system is designed for autonomous vehicles (AVs), which
aims to make AVs better integrate into the human transportation systems and mitigate …

The newly formed hybrid traffic flow where Human-driven Vehicles (HV) share roads with
Autonomous Vehicles (AV) is a foreseeable trend in the modern transportation system …

The integration of Autonomous Vehicles (AVs) into existing human-driven traffic systems
poses considerable challenges, especially within environments where human and machine …

Interaction‐aware autonomous driving (IAAD) is a rapidly growing field of research that
focuses on the development of autonomous vehicles (AVs) that are capable of interacting …

Interacting with surrounding road users is a key feature of autonomous vehicles and is
critical for their intelligence testing. Existing interaction modalities in autonomous vehicle …

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

Unsignalized intersection driving is challenging for automated vehicles. For safe and
efficient performances, the diverse and dynamic behaviors of interacting vehicles should be …

Considering that human-driven vehicles and autonomous vehicles (AVs) will coexist on
roads in the future for a long time, how to merge AVs into human drivers' traffic ecology and …

Uncontrolled intersections with interaction and uncertainties are challenging for autonomous
vehicles (AV) to manage. In this work, we propose a decision-making model specific to …