[HTML][HTML] A comprehensive survey on the application of deep and reinforcement learning approaches in autonomous driving
Abstract Recent advances in Intelligent Transport Systems (ITS) and Artificial Intelligence
(AI) have stimulated and paved the way toward the widespread introduction of Autonomous …
(AI) have stimulated and paved the way toward the widespread introduction of Autonomous …
A survey on data-driven scenario generation for automated vehicle testing
Automated driving is a promising tool for reducing traffic accidents. While some companies
claim that many cutting-edge automated driving functions have been developed, how to …
claim that many cutting-edge automated driving functions have been developed, how to …
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 …
Multimodal end-to-end autonomous driving
A crucial component of an autonomous vehicle (AV) is the artificial intelligence (AI) is able to
drive towards a desired destination. Today, there are different paradigms addressing the …
drive towards a desired destination. Today, there are different paradigms addressing the …
Imitation learning for agile autonomous driving
We present an end-to-end imitation learning system for agile, off-road autonomous driving
using only low-cost on-board sensors. By imitating a model predictive controller equipped …
using only low-cost on-board sensors. By imitating a model predictive controller equipped …
Effective adaptation in multi-task co-training for unified autonomous driving
Aiming towards a holistic understanding of multiple downstream tasks simultaneously, there
is a need for extracting features with better transferability. Though many latest self …
is a need for extracting features with better transferability. Though many latest self …
A human-like trajectory planning method on a curve based on the driver preview mechanism
J Zhao, D Song, B Zhu, Z Sun, J Han… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
With the development of intelligent vehicle technology, many studies have been focused on
developing human-like trajectory planning methods for automated driving systems. Although …
developing human-like trajectory planning methods for automated driving systems. Although …
A multi-neural network acceleration architecture
A cost-effective multi-tenant neural network execution is becoming one of the most important
design goals for modern neural network accelerators. For example, as emerging AI services …
design goals for modern neural network accelerators. For example, as emerging AI services …
Neuromorphic computing chip with spatiotemporal elasticity for multi-intelligent-tasking robots
S Ma, J Pei, W Zhang, G Wang, D Feng, F Yu… - Science Robotics, 2022 - science.org
Recent advances in artificial intelligence have enhanced the abilities of mobile robots in
dealing with complex and dynamic scenarios. However, to enable computationally intensive …
dealing with complex and dynamic scenarios. However, to enable computationally intensive …
Evaluating uncertainty quantification in end-to-end autonomous driving control
R Michelmore, M Kwiatkowska, Y Gal - arXiv preprint arXiv:1811.06817, 2018 - arxiv.org
A rise in popularity of Deep Neural Networks (DNNs), attributed to more powerful GPUs and
widely available datasets, has seen them being increasingly used within safety-critical …
widely available datasets, has seen them being increasingly used within safety-critical …