Recent advancements in end-to-end autonomous driving using deep learning: A survey
End-to-End driving is a promising paradigm as it circumvents the drawbacks associated with
modular systems, such as their overwhelming complexity and propensity for error …
modular systems, such as their overwhelming complexity and propensity for error …
A survey of end-to-end driving: Architectures and training methods
A Tampuu, T Matiisen, M Semikin… - … on Neural Networks …, 2020 - ieeexplore.ieee.org
Autonomous driving is of great interest to industry and academia alike. The use of machine
learning approaches for autonomous driving has long been studied, but mostly in the …
learning approaches for autonomous driving has long been studied, but mostly in the …
End-to-end autonomous driving: Challenges and frontiers
The autonomous driving community has witnessed a rapid growth in approaches that
embrace an end-to-end algorithm framework, utilizing raw sensor input to generate vehicle …
embrace an end-to-end algorithm framework, utilizing raw sensor input to generate vehicle …
[HTML][HTML] An end-to-end deep neural network for autonomous driving designed for embedded automotive platforms
In this paper, one solution for an end-to-end deep neural network for autonomous driving is
presented. The main objective of our work was to achieve autonomous driving with a light …
presented. The main objective of our work was to achieve autonomous driving with a light …
Deep learning for safe autonomous driving: Current challenges and future directions
Advances in information and signal processing technologies have a significant impact on
autonomous driving (AD), improving driving safety while minimizing the efforts of human …
autonomous driving (AD), improving driving safety while minimizing the efforts of human …
A survey of deep learning techniques for autonomous driving
The last decade witnessed increasingly rapid progress in self‐driving vehicle technology,
mainly backed up by advances in the area of deep learning and artificial intelligence (AI) …
mainly backed up by advances in the area of deep learning and artificial intelligence (AI) …
A review of end-to-end autonomous driving in urban environments
D Coelho, M Oliveira - Ieee Access, 2022 - ieeexplore.ieee.org
Autonomous driving in urban environments requires intelligent systems that are able to deal
with complex and unpredictable scenarios. Traditional modular approaches focus on …
with complex and unpredictable scenarios. Traditional modular approaches focus on …
[HTML][HTML] End-to-end autonomous driving through dueling double deep Q-network
Recent years have seen the rapid development of autonomous driving systems, which are
typically designed in a hierarchical architecture or an end-to-end architecture. The …
typically designed in a hierarchical architecture or an end-to-end architecture. The …
[HTML][HTML] Vision-based autonomous vehicle systems based on deep learning: A systematic literature review
In the past decade, autonomous vehicle systems (AVS) have advanced at an exponential
rate, particularly due to improvements in artificial intelligence, which have had a significant …
rate, particularly due to improvements in artificial intelligence, which have had a significant …
Think twice before driving: Towards scalable decoders for end-to-end autonomous driving
End-to-end autonomous driving has made impressive progress in recent years. Existing
methods usually adopt the decoupled encoder-decoder paradigm, where the encoder …
methods usually adopt the decoupled encoder-decoder paradigm, where the encoder …