… attention module is proposed to predict the future locations of the vehicle. We show that the
proposed lane representation together with the lane attention module can be integrated into …

… for autonomous vehicles to know each lane’s exact position, which is the goal of lane …
To address that problem, we propose an attention mechanism that acts on the local features …

… We collected traffic data in urban areas using our autonomous vehicles built on Lincoln
MKZs, equipped with Velodyne HDL-64E LiDAR and Leopard LI-USB30AZ023WDRB cameras. …

… for creating fully autonomous vehicles. Recent ad… lane change actions can be learned.
We also apply temporal and spatial attention to the DRL architecture, which helps the vehicle …

… Accurate prediction of lane-changing (LC) trajectories can … vehicles (ICVs) and connected
autonomous vehicles (CAVs). … prediction model based on an attention-aided encoder-decoder …

… Self-Attention Distillation is used in this paper to improve the network's feature representation
capabilities without adding inference time. The input photos can be correctly processed in …

… -based lane detection algorithm is one of the key technologies in autonomous vehicles. …
high performance in lane detection, but it is still difficult to accurately detect lanes in challenging …

… vehicle in the cruising lane (ie, the outside lane of a two-lane … state of drivers riding in
autonomous vehicles at Level 3 is … drivers’ attention while riding in autonomous vehicles in a …

… ] where the attention mechanism is applied on each 1D vector of surrounding vehicles’ states,
we propose a spatial attention … vehicles for autonomous vehicles,” in 2016 IEEE Intelligent …

Lane detection, as one of the most important core functions in the autonomous driving … In
particular, pursuing high accuracy in complex scenes, such as no line and multiple lane …