This paper presents a novel integrated approach to deal with the decision making and
motion planning for lane-change maneuvers of autonomous vehicle (AV) considering social …

Autonomous decision making is a critical and difficult task for intelligent vehicles in dynamic
transportation environments. In this paper, a reinforcement learning approach with value …

In this paper, we propose a decision-making framework for autonomous driving at road
intersections that determines appropriate maneuvers for an autonomous vehicle to navigate …

This paper presents a decision-making framework for automated driving in highway
environments. The framework is capable of reliably, robustly assessing a given highway …

In order to decide a safe and reliable trajectory for autonomous driving vehicles, the threat of
surrounding vehicles need to be assessed quantitatively and consider the potential risk. This …

Tracking and behavior reasoning of surrounding vehicles on a roadway are keys for the
development of automated vehicles and an advanced driver assistance system (ADAS) …

The accuracy of the data is crucial to the real-time prediction of autonomous driving. Due to
factors such as weather and the accuracy of data collection equipment, there frequently exist …

The complexity of advanced driver-assistance systems (ADASs) is steadily increasing. While
the first applications were based on mere warnings, current systems actively intervene in the …

This paper presents a novel curvilinear-coordinate-based approach to improve object and
situation assessment performance for highly automated vehicles under various curved road …

Automated driving within a lane is a fascinating experience already. However, more exiting
but also technically more challenging is to dare the next step of automating tactical behavior …