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 …

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

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

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 …

A major challenge for autonomous vehicles is interacting with other traffic participants safely
and smoothly. A promising approach to handle such traffic interactions is equipping …

A major challenge for autonomous vehicles is handling interactions with human-driven
vehicles—for example, in highway merging. A better understanding and computational …

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 …

Motion control algorithms in the presence of pedestrians are critical for the development of
safe and reliable Autonomous Vehicles (AVs). Traditional motion control algorithms rely on …

With rapid advances in the field of autonomous vehicles (AVs), the ways in which human–
vehicle interaction (HVI) will take place inside the vehicle have attracted major interest and …

Driver behavior models have been used as input to self-coaching, accident prevention
studies, and developing driver-assisting systems. In recent years, driver behavior …