A review on autonomous vehicles: Progress, methods and challenges

D Parekh, N Poddar, A Rajpurkar, M Chahal, N Kumar… - Electronics, 2022 - mdpi.com
Vehicular technology has recently gained increasing popularity, and autonomous driving is
a hot topic. To achieve safe and reliable intelligent transportation systems, accurate …

Perception and sensing for autonomous vehicles under adverse weather conditions: A survey

Y Zhang, A Carballo, H Yang, K Takeda - ISPRS Journal of …, 2023 - Elsevier
Abstract Automated Driving Systems (ADS) open up a new domain for the automotive
industry and offer new possibilities for future transportation with higher efficiency and …

Milestones in autonomous driving and intelligent vehicles: Survey of surveys

L Chen, Y Li, C Huang, B Li, Y Xing… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
Interest in autonomous driving (AD) and intelligent vehicles (IVs) is growing at a rapid pace
due to the convenience, safety, and economic benefits. Although a number of surveys have …

Sensor and sensor fusion technology in autonomous vehicles: A review

DJ Yeong, G Velasco-Hernandez, J Barry, J Walsh - Sensors, 2021 - mdpi.com
With the significant advancement of sensor and communication technology and the reliable
application of obstacle detection techniques and algorithms, automated driving is becoming …

St-p3: End-to-end vision-based autonomous driving via spatial-temporal feature learning

S Hu, L Chen, P Wu, H Li, J Yan, D Tao - European Conference on …, 2022 - Springer
Many existing autonomous driving paradigms involve a multi-stage discrete pipeline of
tasks. To better predict the control signals and enhance user safety, an end-to-end approach …

A survey on multimodal large language models for autonomous driving

C Cui, Y Ma, X Cao, W Ye, Y Zhou… - Proceedings of the …, 2024 - openaccess.thecvf.com
With the emergence of Large Language Models (LLMs) and Vision Foundation Models
(VFMs), multimodal AI systems benefiting from large models have the potential to equally …

[HTML][HTML] Deep learning for object detection and scene perception in self-driving cars: Survey, challenges, and open issues

A Gupta, A Anpalagan, L Guan, AS Khwaja - Array, 2021 - Elsevier
This article presents a comprehensive survey of deep learning applications for object
detection and scene perception in autonomous vehicles. Unlike existing review papers, we …

Offline reinforcement learning: Tutorial, review, and perspectives on open problems

S Levine, A Kumar, G Tucker, J Fu - arXiv preprint arXiv:2005.01643, 2020 - arxiv.org
In this tutorial article, we aim to provide the reader with the conceptual tools needed to get
started on research on offline reinforcement learning algorithms: reinforcement learning …

Bridging offline reinforcement learning and imitation learning: A tale of pessimism

P Rashidinejad, B Zhu, C Ma, J Jiao… - Advances in Neural …, 2021 - proceedings.neurips.cc
Offline (or batch) reinforcement learning (RL) algorithms seek to learn an optimal policy from
a fixed dataset without active data collection. Based on the composition of the offline dataset …

[HTML][HTML] Autonomous driving architectures: insights of machine learning and deep learning algorithms

MR Bachute, JM Subhedar - Machine Learning with Applications, 2021 - Elsevier
Abstract Research in Autonomous Driving is taking momentum due to the inherent
advantages of autonomous driving systems. The main advantage being the disassociation …