Planning-oriented autonomous driving
Modern autonomous driving system is characterized as modular tasks in sequential order,
ie, perception, prediction, and planning. In order to perform a wide diversity of tasks and …
ie, perception, prediction, and planning. In order to perform a wide diversity of tasks and …
A systematic survey of control techniques and applications in connected and automated vehicles
Vehicle control is one of the most critical challenges in autonomous vehicles (AVs) and
connected and automated vehicles (CAVs), and it is paramount in vehicle safety, passenger …
connected and automated vehicles (CAVs), and it is paramount in vehicle safety, passenger …
Gameformer: Game-theoretic modeling and learning of transformer-based interactive prediction and planning for autonomous driving
Autonomous vehicles operating in complex real-world environments require accurate
predictions of interactive behaviors between traffic participants. This paper tackles the …
predictions of interactive behaviors between traffic participants. This paper tackles the …
Conditional predictive behavior planning with inverse reinforcement learning for human-like autonomous driving
Making safe and human-like decisions is an essential capability of autonomous driving
systems, and learning-based behavior planning presents a promising pathway toward …
systems, and learning-based behavior planning presents a promising pathway toward …
Safety-balanced driving-style aware trajectory planning in intersection scenarios with uncertain environment
X Wang, K Tang, X Dai, J Xu, J Xi, R Ai… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
This paper proposes a two-stage trajectory planning method for self-driving vehicles (SDVs)
in intersection scenarios with uncertain social circumstances while considering other traffic …
in intersection scenarios with uncertain social circumstances while considering other traffic …
Rethinking integration of prediction and planning in deep learning-based automated driving systems: a review
Automated driving has the potential to revolutionize personal, public, and freight mobility.
Besides the enormous challenge of perception, ie accurately perceiving the environment …
Besides the enormous challenge of perception, ie accurately perceiving the environment …
Occworld: Learning a 3d occupancy world model for autonomous driving
Understanding how the 3D scene evolves is vital for making decisions in autonomous
driving. Most existing methods achieve this by predicting the movements of object boxes …
driving. Most existing methods achieve this by predicting the movements of object boxes …
Learning interaction-aware motion prediction model for decision-making in autonomous driving
Predicting the behaviors of other road users is crucial to safe and intelligent decision-making
for autonomous vehicles (AVs). However, most motion prediction models ignore the …
for autonomous vehicles (AVs). However, most motion prediction models ignore the …
DME-Driver: Integrating human decision logic and 3D scene perception in autonomous driving
In the field of autonomous driving, two important features of autonomous driving car systems
are the explainability of decision logic and the accuracy of environmental perception. This …
are the explainability of decision logic and the accuracy of environmental perception. This …
Summary and Reflections on Pedestrian Trajectory Prediction in the Field of Autonomous Driving
Z Fu, K Jiang, C Xie, Y Xu, J Huang… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Pedestrian trajectory prediction is a classic and challenging scientific task that involves
complex engineering science and human factors. These challenges have spurred a …
complex engineering science and human factors. These challenges have spurred a …