mlsanityData to 7 Oct 2026

Learning Interaction-aware Motion Prediction Model for Decision-making in Autonomous Driving

arXiv 2302.03939 ↗First posted 8 Feb 2023cs.ROcited by 6

On the map: End-to-end autonomous driving → Imitation-learning end-to-end planners

Abstract (arXiv)

Predicting the behaviors of other road users is crucial to safe and intelligent decision-making for autonomous vehicles (AVs). However, most motion prediction models ignore the influence of the AV's actions and the planning module has to treat other agents as unalterable moving obstacles. To address this problem, this paper proposes an interaction-aware motion prediction model that is able to predict other agents' future trajectories according to the ego agent's future plan, i.e., their reactions to the ego's actions. Specifically, we employ Transformers to effectively encode the driving scene and incorporate the AV's plan in decoding the predicted trajectories. To train the model to accurately predict the reactions of other agents, we develop an online learning framework, where the ego agent explores the environment and collects other agents' reactions to itself. We validate the decision-making and learning framework in three highly interactive simulated driving scenarios. The results reveal that our decision-making method significantly outperforms the reinforcement learning methods in terms of data efficiency and performance. We also find that using the interaction-aware model can bring better performance than the non-interaction-aware model and the exploration process helps improve the success rate in testing.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Placed in Imitation-learning end-to-end planners, one of 9 directions in End-to-end autonomous driving. Builds on 28 of its 42 references that are in the map. First posted on arXiv 8 Feb 2023.

Builds on

28 of 42 references.

Closest ancestors · 2

Same direction, newest first

  1. 2022Conditional Predictive Behavior Planning with Inverse Reinforcement Learning for Human-like Autonomous Driving17 Dec
  2. 2022Differentiable Integrated Motion Prediction and Planning with Learnable Cost Function for Autonomous Driving21 Jul

Other references · 26

  1. 2017Proximal Policy Optimization Algorithmscited by 14,441
  2. 2018Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actorcited by 4,635
  3. 2018Addressing Function Approximation Error in Actor-Critic Methodscited by 2,302
  4. 2020Deep Reinforcement Learning for Autonomous Driving: A Surveycited by 698
  5. 2019Model-Based Reinforcement Learning for Ataricited by 495
  6. 2018ChauffeurNet: Learning to Drive by Imitating the Best and Synthesizing the Worstcited by 391
  7. 2021MultiPath++: Efficient Information Fusion and Trajectory Aggregation for Behavior Predictioncited by 246
  8. 2018Algorithmic Framework for Model-based Deep Reinforcement Learning with Theoretical Guaranteescited by 138
  9. 2020SMARTS: Scalable Multi-Agent Reinforcement Learning Training School for Autonomous Drivingcited by 121
  10. 2020PiP: Planning-informed Trajectory Prediction for Autonomous Drivingcited by 80
  11. 2021Multi-modal Motion Prediction with Transformer-based Neural Network for Autonomous Drivingcited by 73
  12. 2022A Survey on Model-based Reinforcement Learningcited by 65
14 more
  1. 2020On the role of planning in model-based deep reinforcement learningcited by 57
  2. 2019Model-Predictive Policy Learning with Uncertainty Regularization for Driving in Dense Trafficcited by 50
  3. 2019Deep Imitation Learning for Autonomous Driving in Generic Urban Scenarios with Enhanced Safetycited by 48
  4. 2021Identifying Driver Interactions via Conditional Behavior Predictioncited by 48
  5. 2020Driving Behavior Modeling using Naturalistic Human Driving Data with Inverse Reinforcement Learningcited by 46
  6. 2021Efficient Deep Reinforcement Learning with Imitative Expert Priors for Autonomous Drivingcited by 46
  7. 2020Multi-modal Sensor Fusion-Based Deep Neural Network for End-to-end Autonomous Driving with Scene Understandingcited by 42
  8. 2022Deep Interactive Motion Prediction and Planning: Playing Games with Motion Prediction Modelscited by 27
  9. 2021Improved Deep Reinforcement Learning with Expert Demonstrations for Urban Autonomous Drivingcited by 26
  10. 2022Augmenting Reinforcement Learning with Transformer-based Scene Representation Learning for Decision-making of Autonomous Drivingcited by 24
  11. 2021Prioritized Experience-based Reinforcement Learning with Human Guidance for Autonomous Drivingcited by 21
  12. 2022ReCoAt: A Deep Learning-based Framework for Multi-Modal Motion Prediction in Autonomous Driving Applicationcited by 9
  13. 2022Interventional Behavior Prediction: Avoiding Overly Confident Anticipation in Interactive Predictioncited by 8
  14. 2022Separating the World and Ego Models for Self-Drivingcited by 4

Built on by

Cited by year

Citing papers per year: 2023: 2; 2024: 2; 2025: 2.

6 papers.

  1. 2023DTPP: Differentiable Joint Conditional Prediction and Cost Evaluation for Tree Policy Planning in Autonomous Drivingcited by 46
  2. 2024Hybrid-Prediction Integrated Planning for Autonomous Drivingcited by 18
  3. 2023InteRACT: Transformer Models for Human Intent Prediction Conditioned on Robot Actionscited by 10
  4. 2025A Review of Learning-Based Motion Planning: Toward a Data-Driven Optimal Control Approachcited by 1
  5. 2024S4TP: Social-Suitable and Safety-Sensitive Trajectory Planning for Autonomous Vehiclescited by 0
  6. 2025Goal-conditioned Hierarchical Reinforcement Learning for Sample-efficient and Safe Autonomous Driving at Intersectionscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2023GameFormer: Game-theoretic Modeling and Learning of Transformer-based Interactive Prediction and Planning for Autonomous Driving
  2. 2023Interaction-Aware Trajectory Planning for Autonomous Vehicles with Analytic Integration of Neural Networks into Model Predictive Control
  3. 2023PPAD: Iterative Interactions of Prediction and Planning for End-to-end Autonomous Driving
  4. 2021Scene Transformer: A unified architecture for predicting multiple agent trajectories
  5. 2021Instance-Aware Predictive Navigation in Multi-Agent Environments
  6. 2023Human-Like Implicit Intention Expression for Autonomous Driving Motion Planning: A Method Based on Learning Human Intention Priors
  7. 2018Probabilistic Prediction of Interactive Driving Behavior via Hierarchical Inverse Reinforcement Learning
  8. 2018Towards a Fatality-Aware Benchmark of Probabilistic Reaction Prediction in Highly Interactive Driving Scenarios