No human drives a car in a vacuum; she/he must negotiate with other road users to achieve
their goals in social traffic scenes. A rational human driver can interact with other road users …

Human drivers have different driving styles, experiences, and emotions due to unique
driving characteristics, exhibiting their own driving behaviors and habits. Various research …

Academic research in the field of autonomous vehicles has reached high popularity in
recent years related to several topics as sensor technologies, V2X communications, safety …

Autonomous driving (AD) agents generate driving policies based on online perception
results, which are obtained at multiple levels of abstraction, eg, behavior planning, motion …

On-ramp merging is a challenging task for autonomous vehicles (AVs), especially in mixed
traffic where AVs coexist with human-driven vehicles (HDVs). In this paper, we formulate the …

Reinforcement learning has demonstrated its potential in a series of challenging domains.
However, many real-world decision making tasks involve unpredictable environmental …

Merging is, in general, a challenging task for both human drivers and autonomous vehicles,
especially in dense traffic, because the merging vehicle typically needs to interact with other …

High-speed highway on-ramp merging is a significant challenge toward realizing fully
automated driving (level 4). Connected Autonomous Vehicles (CAVs), that combine …

Intersections are considered one of the most complex scenarios in a self-driving framework
due to the uncertainty in the behaviors of surrounding vehicles and the different types of …

This paper presents a real-time lane change control framework of autonomous driving in
dense Traffic, which exploits cooperative behaviors of other drivers. This paper focuses on …