This study proposes a vehicle platooning algorithm to minimize the disruption from a lane-
changing maneuver. Towards achieving this objective, while most studies emphasize the …

Lane changing behavior is one of the most essential and complex driving attributes. The
lack of proper lane changing behavior can lead to collisions and traffic congestion. In this …

Merging into dense highway traffic for an autonomous vehicle is a complex decision-making
task, wherein the vehicle must identify a potential gap and coordinate with surrounding …

Driving at an unsignalized roundabout is a complex traffic scenario that requires both traffic
safety and efficiency. At the unsignalized roundabout, the driving policy does not simply …

This paper proposes a reinforcement learning-based framework for mandatory lane
changing of automated vehicles in a non-cooperative environment. The objective is to create …

To further enhance decision making in autonomous vehicles field, grant more safety,
comfort, reduce traffic, and accidents, learning approaches were adopted, mainly …

Obstacle avoidance path planning in a dynamic circumstance is one of the fundamental
problems of autonomous vehicles, counting optional maneuvers: emergency braking and …

In order to make the complex driving task of merging safer, in this paper we consider the
automated merging of an autonomous vehicle into a mixed-traffic flow scenario (ie, traffic …

Deep Reinforcement Learning (DRL) methods are inefficient in the initial strategy
exploration process due to the huge state space and action space in large-scale complex …

A ramp merging decision as an important part of the lane change model plays a crucial role
in the efficiency and safety of the entire merging process. However, due to the inevitability of …