mlsanityData to 7 Oct 2026

Milestones in Autonomous Driving and Intelligent Vehicles Part I: Control, Computing System Design, Communication, HD Map, Testing, and Human Behaviors

arXiv 2305.11239 ↗First posted 12 May 2023cs.AI cs.RO cs.SYcited by 25

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Abstract (arXiv)

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 reviewed research achievements in this field, they are still limited in specific tasks and lack systematic summaries and research directions in the future. Our work is divided into 3 independent articles and the first part is a Survey of Surveys (SoS) for total technologies of AD and IVs that involves the history, summarizes the milestones, and provides the perspectives, ethics, and future research directions. This is the second part (Part I for this technical survey) to review the development of control, computing system design, communication, High Definition map (HD map), testing, and human behaviors in IVs. In addition, the third part (Part II for this technical survey) is to review the perception and planning sections. The objective of this paper is to involve all the sections of AD, summarize the latest technical milestones, and guide abecedarians to quickly understand the development of AD and IVs. Combining the SoS and Part II, we anticipate that this work will bring novel and diverse insights to researchers and abecedarians, and serve as a bridge between past and future.

Key facts. Cited by 25 papers in the map (data through 7 Oct 2026). Builds on 31 of its 172 references that are in the map. First posted on arXiv 12 May 2023.

Builds on

31 of 172 references.

References · 31

  1. 2016Driving in the Matrix: Can Virtual Worlds Replace Human-Generated Annotations for Real World Tasks?cited by 194
  2. 2020Deep Learning for LiDAR Point Clouds in Autonomous Driving: A Reviewcited by 114
  3. 2023Motion Planning for Autonomous Driving: The State of the Art and Future Perspectivescited by 112
  4. 2020Deep Learning for Image and Point Cloud Fusion in Autonomous Driving: A Reviewcited by 107
  5. 2019A Survey of Deep Learning Applications to Autonomous Vehicle Controlcited by 101
  6. 2021Explainability of deep vision-based autonomous driving systems: Review and challengescited by 80
  7. 2021Explanations in Autonomous Driving: A Surveycited by 80
  8. 2023Milestones in Autonomous Driving and Intelligent Vehicles: Survey of Surveyscited by 75
  9. 2021Explainable Artificial Intelligence for Autonomous Driving: A Comprehensive Overview and Field Guide for Future Research Directionscited by 73
  10. 2020Computing Systems for Autonomous Driving: State-of-the-Art and Challengescited by 47
  11. 2016Accelerated Evaluation of Automated Vehicles Safety in Lane Change Scenarios Based on Importance Sampling Techniquescited by 44
  12. 2018A Reinforcement Learning Based Approach for Automated Lane Change Maneuverscited by 44
19 more
  1. 2022InstaFormer: Instance-Aware Image-to-Image Translation with Transformercited by 28
  2. 2021Corner Cases for Visual Perception in Automated Driving: Some Guidance on Detection Approachescited by 27
  3. 2019Testing Scenario Library Generation for Connected and Automated Vehicles, Part I: Methodologycited by 24
  4. 2017Autonomous Braking System via Deep Reinforcement Learningcited by 18
  5. 2017End-to-End Deep Learning for Steering Autonomous Vehicles Considering Temporal Dependenciescited by 16
  6. 2021Towards Optimal Strategies for Training Self-Driving Perception Models in Simulationcited by 12
  7. 2020A Vision of C-V2X: Technologies, Field Testing and Challenges with Chinese Developmentcited by 11
  8. 2019Testing Scenario Library Generation for Connected and Automated Vehicles, Part II: Case Studiescited by 10
  9. 2019A Game-Theoretic Framework for Autonomous Vehicles Velocity Control: Bridging Microscopic Differential Games and Macroscopic Mean Field Gamescited by 9
  10. 2019A Survey on Resource Allocation in Vehicular Networkscited by 9
  11. 2020Securing Vehicle-to-Everything (V2X) Communication Platformscited by 9
  12. 2020Control Strategies for Autonomous Vehiclescited by 8
  13. 2021Machine Learning for Security in Vehicular Networks: A Comprehensive Surveycited by 7
  14. 2016Optimal Control for Speed Harmonization of Automated Vehiclescited by 3
  15. 2017Evaluation of Lane Departure Correction Systems Using a Stochastic Driver Modelcited by 2
  16. 2020Radar networks: A review of features and challengescited by 2
  17. 2021Applications of Game Theory in Vehicular Networks: A Surveycited by 2
  18. 2018Map matching when the map is wrong: Efficient vehicle tracking on- and off-road for map learningcited by 1
  19. 2020Survey on Congestion Detection and Control in Connected Vehiclescited by 1

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 8; 2024: 9; 2025: 5; 2026: 3.

25 papers.

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  1. 2023DiLu: A Knowledge-Driven Approach to Autonomous Driving with Large Language Modelscited by 204
  2. 2023LanguageMPC: Large Language Models as Decision Makers for Autonomous Drivingcited by 188
  3. 2023Drive Like a Human: Rethinking Autonomous Driving with Large Language Modelscited by 158
  4. 2024DriveArena: A Closed-loop Generative Simulation Platform for Autonomous Drivingcited by 98
  5. 2024Multi-Agent Reinforcement Learning for Autonomous Driving: A Surveycited by 30
  6. 2024KoMA: Knowledge-driven Multi-agent Framework for Autonomous Driving with Large Language Modelscited by 16
  7. 2025InsightDrive: Insight Scene Representation for End-to-End Autonomous Drivingcited by 14
  8. 2023Deep Transfer Learning for Intelligent Vehicle Perception: a Surveycited by 10
  9. 2023Milestones in Autonomous Driving and Intelligent Vehicles Part II: Perception and Planningcited by 9
  10. 2024Large Language Model guided Deep Reinforcement Learning for Decision Making in Autonomous Drivingcited by 8
  11. 2023FusionPlanner: A Multi-task Motion Planner for Mining Trucks via Multi-sensor Fusioncited by 7
  12. 2024Long and Short-Term Constraints Driven Safe Reinforcement Learning for Autonomous Drivingcited by 4
13 more
  1. 2024A Survey on Large Language Model-empowered Autonomous Drivingcited by 3
  2. 2025Vision-Centric 4D Occupancy Forecasting and Planning via Implicit Residual World Modelscited by 3
  3. 2025VLM-UDMC: VLM-Enhanced Unified Decision-Making and Motion Control for Urban Autonomous Drivingcited by 2
  4. 2023AIR: Threats of Adversarial Attacks on Deep Learning-Based Information Recoverycited by 1
  5. 2023Enhancing Cross-Dataset Performance of Distracted Driving Detection With Score Softmax Classifier And Dynamic Gaussian Smoothing Supervisioncited by 1
  6. 2024Compositionally Safe Construction of Autonomous Driving Systemscited by 1
  7. 2025Maps for Autonomous Driving: Full-process Survey and Frontierscited by 1
  8. 2024Scenarios Engineering driven Autonomous Transportation in Open-Pit Minescited by 0
  9. 2024On-Road Object Importance Estimation: A New Dataset and A Model with Multi-Fold Top-Down Guidancecited by 0
  10. 2025Towards a Reward-Free Reinforcement Learning Framework for Vehicle Controlcited by 0
  11. 2026Self-Explainability in Self-Adaptive and Self-Organising Systems: Status and Research Directionscited by 0
  12. 2026AI Control Scientist: LLM-driven Agentic System for Automated Control Designcited by 0
  13. 2026A Survey on End-to-End Autonomous Driving Training from the Perspectives of Data, Strategy, and Platformcited by 0