mlsanityData to 7 Oct 2026

Autonomous Driving with Deep Learning: A Survey of State-of-Art Technologies

arXiv 2006.06091 ↗First posted 10 Jun 2020cs.CVcited by 41

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Abstract (arXiv)

Since DARPA Grand Challenges (rural) in 2004/05 and Urban Challenges in 2007, autonomous driving has been the most active field of AI applications. Almost at the same time, deep learning has made breakthrough by several pioneers, three of them (also called fathers of deep learning), Hinton, Bengio and LeCun, won ACM Turin Award in 2019. This is a survey of autonomous driving technologies with deep learning methods. We investigate the major fields of self-driving systems, such as perception, mapping and localization, prediction, planning and control, simulation, V2X and safety etc. Due to the limited space, we focus the analysis on several key areas, i.e. 2D and 3D object detection in perception, depth estimation from cameras, multiple sensor fusion on the data, feature and task level respectively, behavior modelling and prediction of vehicle driving and pedestrian trajectories.

Key facts. Cited by 41 papers in the map (data through 7 Oct 2026). First posted on arXiv 10 Jun 2020.

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Citing papers per year: 2021: 4; 2022: 7; 2023: 12; 2024: 9; 2025: 6; 2026: 3.

41 papers.

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  1. 2021Deep Deterministic Uncertainty: A Simple Baselinecited by 200
  2. 2023Milestones in Autonomous Driving and Intelligent Vehicles: Survey of Surveyscited by 75
  3. 2023ViDA: Homeostatic Visual Domain Adapter for Continual Test Time Adaptationcited by 58
  4. 2022Tensor Program Optimization with Probabilistic Programscited by 30
  5. 2021Deep Deterministic Uncertainty for Semantic Segmentationcited by 24
  6. 2023Mitigating Transformer Overconfidence via Lipschitz Regularizationcited by 15
  7. 2023Applications of Large Scale Foundation Models for Autonomous Drivingcited by 14
  8. 2022Neural Architecture Search for Dense Prediction Tasks in Computer Visioncited by 11
  9. 2023Deep Transfer Learning for Intelligent Vehicle Perception: a Surveycited by 10
  10. 2024Composite Bayesian Optimization In Function Spaces Using NEON -- Neural Epistemic Operator Networkscited by 10
  11. 2022Joint rotational invariance and adversarial training of a dual-stream Transformer yields state of the art Brain-Score for Area V4cited by 7
  12. 2022LiDAR-as-Camera for End-to-End Drivingcited by 7
29 more
  1. 2024Advancing Deep Active Learning & Data Subset Selection: Unifying Principles with Information-Theory Intuitionscited by 7
  2. 2021A framework for benchmarking uncertainty in deep regressioncited by 4
  3. 2022Visualizing the Diversity of Representations Learned by Bayesian Neural Networkscited by 4
  4. 2022Bimodal Distributed Binarized Neural Networkscited by 4
  5. 2024Exploiting T-norms for Deep Learning in Autonomous Drivingcited by 4
  6. 2024Mapping the Mind of an Instruction-based Image Editing using SMILEcited by 3
  7. 2023A Survey on Datasets for Decision-making of Autonomous Vehiclecited by 2
  8. 2023PM-DETR: Domain Adaptive Prompt Memory for Object Detection with Transformerscited by 2
  9. 2023End-to-end Lidar-Driven Reinforcement Learning for Autonomous Racingcited by 2
  10. 2023Combating the effects of speed and delays in end-to-end self-drivingcited by 2
  11. 2024Forward Learning for Gradient-based Black-box Saliency Map Generationcited by 2
  12. 2021Why Calibration Error is Wrong Given Model Uncertainty: Using Posterior Predictive Checks with Deep Learningcited by 1
  13. 2022On the Relationship Between Adversarial Robustness and Decision Region in Deep Neural Networkscited by 1
  14. 2023A survey on deep learning approaches for data integration in autonomous driving systemcited by 1
  15. 2024PreGSU-A Generalized Traffic Scene Understanding Model for Autonomous Driving based on Pre-trained Graph Attention Networkcited by 1
  16. 2024LaserGuider: A Laser Based Physical Backdoor Attack against Deep Neural Networkscited by 1
  17. 2024Application of Multimodal Large Language Models in Autonomous Drivingcited by 1
  18. 2025From Failures to Fixes: LLM-Driven Scenario Repair for Self-Evolving Autonomous Drivingcited by 1
  19. 2023Conservative Estimation of Perception Relevance of Dynamic Objects for Safe Trajectories in Automotive Scenarioscited by 0
  20. 2023Towards Establishing Systematic Classification Requirements for Automated Drivingcited by 0
  21. 2024Combining Cloud and Mobile Computing for Machine Learningcited by 0
  22. 2025Towards Learning Scalable Agile Dynamic Motion Planning for Robosoccer Teams with Policy Optimizationcited by 0
  23. 2025LimSim Series: An Autonomous Driving Simulation Platform for Validation and Enhancementcited by 0
  24. 2025Logit Disagreement: OoD Detection with Bayesian Neural Networkscited by 0
  25. 2025SKGE-SWIN: End-To-End Autonomous Vehicle Waypoint Prediction and Navigation Using Skip Stage Swin Transformercited by 0
  26. 2025GPU Temperature Simulation-Based Testing for In-Vehicle Deep Learning Frameworkscited by 0
  27. 2026CoDS: Robust Collaborative Perception via Expert-driven Detection and BEV Segmentationcited by 0
  28. 2026Flexible Spectral-Normalized Neural Gaussian Process for Dynamic Aperture Predictioncited by 0
  29. 2026End-to-End Learning vs. Modular Architectures: Comparative Insights into Autonomous Driving Systemscited by 0