Simulation has long been an essential part of testing autonomous driving systems, but only
recently has simulation been useful for building and training self-driving vehicles. Vehicle …

In this paper, we propose a cooperative learning method to acquire the intelligent self-
driving strategy. The intelligent self-driving vehicle can control its velocity by itself to maintain …

Cooperative driving behavior is essential for driving in traffic, especially for ramp merging,
lane changing or navigating intersections. Autonomous vehicles should also manage these …

Autonomous driving vehicles can reduce congestion and improve safety while increasing
traffic efficiency. To reflect the quality of driving more comprehensively, the driving safety …

This study proposes a framework for human-like autonomous car-following planning based
on deep reinforcement learning (deep RL). Historical driving data are fed into a simulation …

Multiple automakers have in development or in production automated driving systems (ADS)
that offer freeway-pilot functions. This type of ADS is typically limited to restricted-access …

Traditional vehicle lane change decision model based on the mathematical model method
and the logical model method is difficult to accurately describe the complete lane changing …

Lane change for autonomous vehicles (AVs) is an important but challenging task in complex
dynamic traffic environments. Due to difficulties in guarantee safety as well as a high …

This paper provides two methods to detect lane changes of the vehicles around the ego
vehicle on highway scenarios. The first method is rule-based with changing lane …

This paper addresses intention and trajectory prediction of exo-vehicles in an urban driving
environment. Urban environments pose challenging scenarios for self-driving cars …