mlsanityData to 14 Oct 2026

A Review of Tracking, Prediction and Decision Making Methods for Autonomous Driving

arXiv 1909.07707 ↗First posted 17 Sep 2019cs.LG stat.MLcited by 17

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Abstract (arXiv)

This literature review focuses on three important aspects of an autonomous car system: tracking (assessing the identity of the actors such as cars, pedestrians or obstacles in a sequence of observations), prediction (predicting the future motion of surrounding vehicles in order to navigate through various traffic scenarios) and decision making (analyzing the available actions of the ego car and their consequences to the entire driving context). For tracking and prediction, approaches based on (deep) neural networks and other, especially stochastic techniques, are reported. For decision making, deep reinforcement learning algorithms are presented, together with methods used to explore different alternative actions, such as Monte Carlo Tree Search.

Key facts. Cited by 17 papers in the map (data through 14 Oct 2026). First posted on arXiv 17 Sep 2019.

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Citing papers per year: 2021: 3; 2022: 3; 2023: 4; 2024: 4; 2025: 3.

17 papers.

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  1. 2023Milestones in Autonomous Driving and Intelligent Vehicles: Survey of Surveyscited by 75
  2. 2021Review of Pedestrian Trajectory Prediction Methods: Comparing Deep Learning and Knowledge-based Approachescited by 30
  3. 2023Machine Learning for Autonomous Vehicle's Trajectory Prediction: A comprehensive survey, Challenges, and Future Research Directionscited by 23
  4. 2022Interpretable Self-Aware Neural Networks for Robust Trajectory Predictioncited by 22
  5. 2024Motion-Grounded Video Reasoning: Understanding and Perceiving Motion at Pixel Levelcited by 19
  6. 2021Decision-Making Technology for Autonomous Vehicles Learning-Based Methods, Applications and Future Outlookcited by 14
  7. 2025Trajectory Prediction for Autonomous Driving: Progress, Limitations, and Future Directionscited by 14
  8. 2023VT-Former: An Exploratory Study on Vehicle Trajectory Prediction for Highway Surveillance through Graph Isomorphism and Transformercited by 10
  9. 2022Relation-based Motion Prediction using Traffic Scene Graphscited by 6
  10. 2022Enhanced method for reinforcement learning based dynamic obstacle avoidance by assessment of collision riskcited by 5
  11. 2024ComTraQ-MPC: Meta-Trained DQN-MPC Integration for Trajectory Tracking with Limited Active Localization Updatescited by 4
  12. 2025RiskNet: Interaction-Aware Risk Forecasting for Autonomous Driving in Long-Tail Scenarioscited by 4
5 more
  1. 2023OccluTrack: Rethinking Awareness of Occlusion for Enhancing Multiple Pedestrian Trackingcited by 3
  2. 2021A Socially Aware Reinforcement Learning Agent for The Single Track Road Problemcited by 0
  3. 2024TrajectoryNAS: A Neural Architecture Search for Trajectory Predictioncited by 0
  4. 2024F1tenth Autonomous Racing With Offline Reinforcement Learning Methodscited by 0
  5. 2025Adversarial Attack for RGB-Event based Visual Object Trackingcited by 0