mlsanityData to 7 Oct 2026

Prediction Based Decision Making for Autonomous Highway Driving

arXiv 2209.02106 ↗First posted 5 Sep 2022cs.RO cs.AIcited by 4

On the map: End-to-end autonomous driving → Reinforcement learning for driving

Abstract (arXiv)

Autonomous driving decision-making is a challenging task due to the inherent complexity and uncertainty in traffic. For example, adjacent vehicles may change their lane or overtake at any time to pass a slow vehicle or to help traffic flow. Anticipating the intention of surrounding vehicles, estimating their future states and integrating them into the decision-making process of an automated vehicle can enhance the reliability of autonomous driving in complex driving scenarios. This paper proposes a Prediction-based Deep Reinforcement Learning (PDRL) decision-making model that considers the manoeuvre intentions of surrounding vehicles in the decision-making process for highway driving. The model is trained using real traffic data and tested in various traffic conditions through a simulation platform. The results show that the proposed PDRL model improves the decision-making performance compared to a Deep Reinforcement Learning (DRL) model by decreasing collision numbers, resulting in safer driving.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Placed in Reinforcement learning for driving, one of 9 directions in End-to-end autonomous driving. Builds on 19 of its 55 references that are in the map. First posted on arXiv 5 Sep 2022.

Builds on

19 of 55 references.

Closest ancestors · 1

Same direction, newest first

  1. 2021Reinforcement Learning Based Safe Decision Making for Highway Autonomous Driving13 May

Other references · 18

  1. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  2. 2017CARLA: An Open Urban Driving Simulatorcited by 2,431
  3. 2015Deep Reinforcement Learning with Double Q-learningcited by 1,704
  4. 2015Dueling Network Architectures for Deep Reinforcement Learningcited by 769
  5. 2017AirSim: High-Fidelity Visual and Physical Simulation for Autonomous Vehiclescited by 517
  6. 2018Implicit Quantile Networks for Distributional Reinforcement Learningcited by 362
  7. 2018The highD Dataset: A Drone Dataset of Naturalistic Vehicle Trajectories on German Highways for Validation of Highly Automated Driving Systemscited by 276
  8. 2017Noisy Networks for Explorationcited by 262
  9. 2017Deep Reinforcement Learning framework for Autonomous Drivingcited by 224
  10. 2014A Convolutional Neural Network for Modelling Sentencescited by 163
  11. 2016Averaged-DQN: Variance Reduction and Stabilization for Deep Reinforcement Learningcited by 106
  12. 2019A Survey of Deep Learning Applications to Autonomous Vehicle Controlcited by 101
6 more
  1. 2019Combining Planning and Deep Reinforcement Learning in Tactical Decision Making for Autonomous Drivingcited by 52
  2. 2019Cooperation-Aware Reinforcement Learning for Merging in Dense Trafficcited by 20
  3. 2019Automated Lane Change Decision Making using Deep Reinforcement Learning in Dynamic and Uncertain Highway Environmentcited by 20
  4. 2019Driving Decision and Control for Autonomous Lane Change based on Deep Reinforcement Learningcited by 14
  5. 2021Early Lane Change Prediction for Automated Driving Systems Using Multi-Task Attention-based Convolutional Neural Networkscited by 10
  6. 2018Risk-averse Behavior Planning for Autonomous Driving under Uncertaintycited by 4

Built on by

Cited by year

Citing papers per year: 2023: 3; 2024: 1.

4 papers.

  1. 2024HighwayLLM: Decision-Making and Navigation in Highway Driving with RL-Informed Language Modelcited by 9
  2. 2023EnduRL: Enhancing Safety, Stability, and Efficiency of Mixed Traffic Under Real-World Perturbations Via Reinforcement Learningcited by 7
  3. 2023Decision Making for Autonomous Driving in Interactive Merge Scenarios via Learning-based Predictioncited by 0
  4. 2023Human-Like Autonomous Driving on Dense Trafficcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025Evaluating Scenario-based Decision-making for Interactive Autonomous Driving Using Rational Criteria: A Survey
  2. 2024Research on Autonomous Driving Decision-making Strategies based Deep Reinforcement Learning
  3. 2025A Hybrid Input based Deep Reinforcement Learning for Lane Change Decision-Making of Autonomous Vehicle
  4. 2023Predictive Maneuver Planning with Deep Reinforcement Learning (PMP-DRL) for comfortable and safe autonomous driving
  5. 2023Machine Learning for Autonomous Vehicle's Trajectory Prediction: A comprehensive survey, Challenges, and Future Research Directions
  6. 2023Safe, Efficient, Comfort, and Energy-saving Automated Driving through Roundabout Based on Deep Reinforcement Learning
  7. 2023Parameterized Decision-making with Multi-modal Perception for Autonomous Driving
  8. 2023Integration of Reinforcement Learning Based Behavior Planning With Sampling Based Motion Planning for Automated Driving