Dual transformer based prediction for lane change intentions and trajectories in mixed traffic environment
In a mixed traffic environment of human and autonomous driving, it is crucial for an
autonomous vehicle to predict the lane change intentions and trajectories of vehicles that …
autonomous vehicle to predict the lane change intentions and trajectories of vehicles that …
Decision-making driven by driver intelligence and environment reasoning for high-level autonomous vehicles: a survey
Autonomous vehicle (AV) is expected to reshape the future transportation system, and its
decision-making is one of the most critical modules. Many current decision-making modules …
decision-making is one of the most critical modules. Many current decision-making modules …
A vectorized representation model for trajectory prediction of intelligent vehicles in challenging scenarios
Trajectory prediction for challenging scenarios has always been a significant problem in the
field due to the complexity of dynamic scenarios and interactions. Furthermore, there is often …
field due to the complexity of dynamic scenarios and interactions. Furthermore, there is often …
Predicting highway lane-changing maneuvers: A benchmark analysis of machine and ensemble learning algorithms
Understanding and predicting highway lane-change maneuvers is essential for driving
modeling and its automation. The development of data-based lane-changing decision …
modeling and its automation. The development of data-based lane-changing decision …
Robust multiagent reinforcement learning toward coordinated decision-making of automated vehicles
Automated driving is essential for develo** and deploying intelligent transportation
systems. However, unavoidable sensor noises or perception errors may cause an …
systems. However, unavoidable sensor noises or perception errors may cause an …
AMGB: Trajectory prediction using attention-based mechanism GCN-BiLSTM in IOV
R Li, Y Qin, J Wang, H Wang - Pattern Recognition Letters, 2023 - Elsevier
Accurate and reliable prediction of vehicle trajectories is closely related to the path planning
of intelligent vehicles and contributes to intelligent transportation safety, especially in …
of intelligent vehicles and contributes to intelligent transportation safety, especially in …
Redformer: Radar enlightens the darkness of camera perception with transformers
Enhancing the accuracy and reliability of perception systems in automated vehicles is
critical, especially under varying driving conditions. Unfortunately, the challenges of adverse …
critical, especially under varying driving conditions. Unfortunately, the challenges of adverse …
Multimodal manoeuvre and trajectory prediction for automated driving on highways using transformer networks
Predicting the behaviour (ie, manoeuvre/trajectory) of other road users, including vehicles, is
critical for the safe and efficient operation of autonomous vehicles (AVs), aka, automated …
critical for the safe and efficient operation of autonomous vehicles (AVs), aka, automated …
3D object detection and tracking based on lidar-camera fusion and IMM-UKF algorithm towards highway driving
C Nie, Z Ju, Z Sun, H Zhang - IEEE Transactions on Emerging …, 2023 - ieeexplore.ieee.org
In this work, we propose DTFI: a 3D object D etection and T racking approach consisting of
lidar-camera F usion-based 3D object detection and I nteracting multiple model with …
lidar-camera F usion-based 3D object detection and I nteracting multiple model with …
Robust multitask learning with sample gradient similarity
Multitask learning has led to great success in many deep learning applications during the
last decade. However, recent experiments have demonstrated that the performance of …
last decade. However, recent experiments have demonstrated that the performance of …