mlsanityData to 7 Oct 2026

Safe, Efficient, and Comfortable Velocity Control based on Reinforcement Learning for Autonomous Driving

arXiv 1902.00089 ↗First posted 29 Jan 2019cs.LG cs.AI cs.ROcited by 56

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Cited by 23 in End-to-end autonomous driving, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

A model used for velocity control during car following was proposed based on deep reinforcement learning (RL). To fulfil the multi-objectives of car following, a reward function reflecting driving safety, efficiency, and comfort was constructed. With the reward function, the RL agent learns to control vehicle speed in a fashion that maximizes cumulative rewards, through trials and errors in the simulation environment. A total of 1,341 car-following events extracted from the Next Generation Simulation (NGSIM) dataset were used to train the model. Car-following behavior produced by the model were compared with that observed in the empirical NGSIM data, to demonstrate the model's ability to follow a lead vehicle safely, efficiently, and comfortably. Results show that the model demonstrates the capability of safe, efficient, and comfortable velocity control in that it 1) has small percentages (8%) of dangerous minimum time to collision values (textless 5s) than human drivers in the NGSIM data (35%); 2) can maintain efficient and safe headways in the range of 1s to 2s; and 3) can follow the lead vehicle comfortably with smooth acceleration. The results indicate that reinforcement learning methods could contribute to the development of autonomous driving systems.

Key facts. Cited by 56 papers in the map (data through 7 Oct 2026). First posted on arXiv 29 Jan 2019.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 4; 2022: 12; 2023: 12; 2024: 19; 2025: 8; 2026: 1.

56 papers.

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  1. 2024HAIM-DRL: Enhanced Human-in-the-loop Reinforcement Learning for Safe and Efficient Autonomous Drivingcited by 31
  2. 2023FollowNet: A Comprehensive Benchmark for Car-Following Behavior Modelingcited by 21
  3. 2024A Review of Reward Functions for Reinforcement Learning in the context of Autonomous Drivingcited by 17
  4. 2024Adversarial Safety-Critical Scenario Generation using Naturalistic Human Driving Priorscited by 15
  5. 2021Reliably-stabilizing piecewise-affine neural network controllerscited by 13
  6. 2025CurricuVLM: Towards Safe Autonomous Driving via Personalized Safety-Critical Curriculum Learning with Vision-Language Modelscited by 11
  7. 2022TransFollower: Long-Sequence Car-Following Trajectory Prediction through Transformercited by 9
  8. 2024Generating and Evolving Reward Functions for Highway Driving with Large Language Modelscited by 8
  9. 2023EnduRL: Enhancing Safety, Stability, and Efficiency of Mixed Traffic Under Real-World Perturbations Via Reinforcement Learningcited by 7
  10. 2023Parameterized Decision-making with Multi-modal Perception for Autonomous Drivingcited by 7
  11. 2021SAINT-ACC: Safety-Aware Intelligent Adaptive Cruise Control for Autonomous Vehicles Using Deep Reinforcement Learningcited by 6
  12. 2022Modeling driver's evasive behavior during safety-critical lane changes:Two-dimensional time-to-collision and deep reinforcement learningcited by 6
38 more
  1. 2023EnsembleFollower: A Hybrid Car-Following Framework Based On Reinforcement Learning and Hierarchical Planningcited by 6
  2. 2025RoaD: Rollouts as Demonstrations for Closed-Loop Supervised Fine-Tuning of Autonomous Driving Policiescited by 6
  3. 2021Hybrid Car-Following Strategy based on Deep Deterministic Policy Gradient and Cooperative Adaptive Cruise Controlcited by 5
  4. 2022Deep Reinforcement Learning Aided Platoon Control Relying on V2X Informationcited by 5
  5. 2023KI-PMF: Knowledge Integrated Plausible Motion Forecastingcited by 5
  6. 2024From Words to Wheels: Automated Style-Customized Policy Generation for Autonomous Drivingcited by 5
  7. 2021Formulation and validation of a car-following model based on deep reinforcement learningcited by 4
  8. 2022Reinforcement Learning with a Terminatorcited by 4
  9. 2022Autonomous Platoon Control with Integrated Deep Reinforcement Learning and Dynamic Programmingcited by 4
  10. 2022Traffic-Aware Autonomous Driving with Differentiable Traffic Simulationcited by 4
  11. 2024MetaFollower: Adaptable Personalized Autonomous Car Followingcited by 4
  12. 2024EditFollower: Tunable Car Following Models for Customizable Adaptive Cruise Control Systemscited by 4
  13. 2022Bilateral Deep Reinforcement Learning Approach for Better-than-human Car Following Modelcited by 3
  14. 2023Safety in Traffic Management Systems: A Comprehensive Surveycited by 3
  15. 2023DeepQTest: Testing Autonomous Driving Systems with Reinforcement Learning and Real-world Weather Datacited by 3
  16. 2025Reinforcement Learning with Continuous Actions Under Unmeasured Confoundingcited by 3
  17. 2025MPCFormer: A physics-informed data-driven approach for explainable socially-aware autonomous drivingcited by 3
  18. 2022Vessel-following model for inland waterways based on deep reinforcement learningcited by 2
  19. 2022A Bibliometric Analysis and Review on Reinforcement Learning for Transportation Applicationscited by 2
  20. 2023Vision-based DRL Autonomous Driving Agent with Sim2Real Transfercited by 2
  21. 2023Multi-Timescale Control and Communications with Deep Reinforcement Learning -- Part I: Communication-Aware Vehicle Controlcited by 2
  22. 2024Communication-Aware Reinforcement Learning for Cooperative Adaptive Cruise Controlcited by 2
  23. 2025A Survey of Reinforcement Learning-Based Motion Planning for Autonomous Driving: Lessons Learned from a Driving Task Perspectivecited by 2
  24. 2022A Safety-Critical Decision Making and Control Framework Combining Machine Learning and Rule-based Algorithmscited by 1
  25. 2024Act Better by Timing: A timing-Aware Reinforcement Learning for Autonomous Drivingcited by 1
  26. 2024GTP-UDrive: Unified Game-Theoretic Trajectory Planner and Decision-Maker for Autonomous Driving in Mixed Traffic Environmentscited by 1
  27. 2024SECRM-2D: RL-Based Efficient and Comfortable Route-Following Autonomous Driving with Analytic Safety Guaranteescited by 1
  28. 2024A Safe Self-evolution Algorithm for Autonomous Driving Based on Data-Driven Risk Quantification Modelcited by 1
  29. 2024Traffic Co-Simulation Framework Empowered by Infrastructure Camera Sensing and Reinforcement Learningcited by 1
  30. 2025Balancing Progress and Safety: A Novel Risk-Aware Objective for RL in Autonomous Drivingcited by 1
  31. 2025TGLD: A Trust-Aware Game-Theoretic Lane-Changing Decision Framework for Automated Vehicles in Heterogeneous Trafficcited by 1
  32. 2026Pedestrian-Aware LLM-Driven Behavioral Planning for Autonomous Vehiclescited by 1
  33. 2022AVDDPG: Federated reinforcement learning applied to autonomous platoon controlcited by 0
  34. 2022Multisymplectic Formulation of Deep Learning Using Mean--Field Type Control and Nonlinear Stability of Training Algorithmcited by 0
  35. 2023Traffic Shaping and Hysteresis Mitigation Using Deep Reinforcement Learning in a Connected Driving Environmentcited by 0
  36. 2023Communication-Efficient Zeroth-Order Distributed Online Optimization: Algorithm, Theory, and Applicationscited by 0
  37. 2023Combining Policy Gradient and Safety-Based Control for Autonomous Drivingcited by 0
  38. 2024Shared learning of powertrain control policies for vehicle fleetscited by 0

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