Decision making of autonomous vehicles in lane change scenarios: Deep reinforcement learning approaches with risk awareness
Driving safety is the most important element that needs to be considered for autonomous
vehicles (AVs). To ensure driving safety, we proposed a lane change decision-making …
vehicles (AVs). To ensure driving safety, we proposed a lane change decision-making …
Lane change strategies for autonomous vehicles: A deep reinforcement learning approach based on transformer
End-to-end approaches are one of the most promising solutions for autonomous vehicles
(AVs) decision-making. However, the deployment of these technologies is usually …
(AVs) decision-making. However, the deployment of these technologies is usually …
Machine Learning-Based Vehicle Intention Trajectory Recognition and Prediction for Autonomous Driving
In recent years, the expansion of internet technology and advancements in automation have
brought significant attention to autonomous driving technology. Major automobile …
brought significant attention to autonomous driving technology. Major automobile …
Automated lane change decision making using deep reinforcement learning in dynamic and uncertain highway environment
Autonomous lane changing is a critical feature for advanced autonomous driving systems,
that involves several challenges such as uncertainty in other driver's behaviors and the trade …
that involves several challenges such as uncertainty in other driver's behaviors and the trade …
A novel lane change decision-making model of autonomous vehicle based on support vector machine
Autonomous driving is a crucial issue of the automobile industry, and research on lane
change is its significant part. Previous works on the autonomous vehicle lane change mainly …
change is its significant part. Previous works on the autonomous vehicle lane change mainly …
Risk assessment based collision avoidance decision-making for autonomous vehicles in multi-scenarios
In this paper, we proposed a new risk assessment based decision-making algorithm to
guarantee collision avoidance in multi-scenarios for autonomous vehicles. A probabilistic …
guarantee collision avoidance in multi-scenarios for autonomous vehicles. A probabilistic …
A co-evolutionary lane-changing trajectory planning method for automated vehicles based on the instantaneous risk identification
J Wu, X Chen, Y Bie, W Zhou - Accident Analysis & Prevention, 2023 - Elsevier
Lane-changing trajectory planning (LTP) is an effective concept to control automated
vehicles (AVs) in mixed traffic, which can reduce traffic conflicts and improve overall traffic …
vehicles (AVs) in mixed traffic, which can reduce traffic conflicts and improve overall traffic …
An integrated model for autonomous speed and lane change decision-making based on deep reinforcement learning
The implementation of autonomous driving is inseparable from developing intelligent driving
decision-making models, which are facing high scene complexity, poor decision-making …
decision-making models, which are facing high scene complexity, poor decision-making …
Automated lane change strategy using proximal policy optimization-based deep reinforcement learning
Lane-change maneuvers are commonly executed by drivers to follow a certain routing plan,
overtake a slower vehicle, adapt to a merging lane ahead, etc. However, improper lane …
overtake a slower vehicle, adapt to a merging lane ahead, etc. However, improper lane …
Lane change decision-making through deep reinforcement learning with rule-based constraints
Autonomous driving decision-making is a great challenge due to the complexity and
uncertainty of the traffic environment. Combined with the rule-based constraints, a Deep Q …
uncertainty of the traffic environment. Combined with the rule-based constraints, a Deep Q …