A survey of deep learning applications to autonomous vehicle control
Designing a controller for autonomous vehicles capable of providing adequate performance
in all driving scenarios is challenging due to the highly complex environment and inability to …
in all driving scenarios is challenging due to the highly complex environment and inability to …
A survey on imitation learning techniques for end-to-end autonomous vehicles
The state-of-the-art decision and planning approaches for autonomous vehicles have
moved away from manually designed systems, instead focusing on the utilisation of large …
moved away from manually designed systems, instead focusing on the utilisation of large …
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 …
Behavior Transformers: Cloning modes with one stone
NM Shafiullah, Z Cui… - Advances in neural …, 2022 - proceedings.neurips.cc
While behavior learning has made impressive progress in recent times, it lags behind
computer vision and natural language processing due to its inability to leverage large …
computer vision and natural language processing due to its inability to leverage large …
Safety-enhanced autonomous driving using interpretable sensor fusion transformer
Large-scale deployment of autonomous vehicles has been continually delayed due to safety
concerns. On the one hand, comprehensive scene understanding is indispensable, a lack of …
concerns. On the one hand, comprehensive scene understanding is indispensable, a lack of …
Transfuser: Imitation with transformer-based sensor fusion for autonomous driving
How should we integrate representations from complementary sensors for autonomous
driving? Geometry-based fusion has shown promise for perception (eg, object detection …
driving? Geometry-based fusion has shown promise for perception (eg, object detection …
Multi-modal fusion transformer for end-to-end autonomous driving
How should representations from complementary sensors be integrated for autonomous
driving? Geometry-based sensor fusion has shown great promise for perception tasks such …
driving? Geometry-based sensor fusion has shown great promise for perception tasks such …
Model-based imitation learning for urban driving
An accurate model of the environment and the dynamic agents acting in it offers great
potential for improving motion planning. We present MILE: a Model-based Imitation …
potential for improving motion planning. We present MILE: a Model-based Imitation …
Trajectory-guided control prediction for end-to-end autonomous driving: A simple yet strong baseline
Current end-to-end autonomous driving methods either run a controller based on a planned
trajectory or perform control prediction directly, which have spanned two separately studied …
trajectory or perform control prediction directly, which have spanned two separately studied …
Vad: Vectorized scene representation for efficient autonomous driving
Autonomous driving requires a comprehensive understanding of the surrounding
environment for reliable trajectory planning. Previous works rely on dense rasterized scene …
environment for reliable trajectory planning. Previous works rely on dense rasterized scene …