mlsanityData to 14 Oct 2026

D2-TPred: Discontinuous Dependency for Trajectory Prediction under Traffic Lights

arXiv 2207.10398 ↗First posted 21 Jul 2022cs.CVcited by 10

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Abstract (arXiv)

A profound understanding of inter-agent relationships and motion behaviors is important to achieve high-quality planning when navigating in complex scenarios, especially at urban traffic intersections. We present a trajectory prediction approach with respect to traffic lights, D2-TPred, which uses a spatial dynamic interaction graph (SDG) and a behavior dependency graph (BDG) to handle the problem of discontinuous dependency in the spatial-temporal space. Specifically, the SDG is used to capture spatial interactions by reconstructing sub-graphs for different agents with dynamic and changeable characteristics during each frame. The BDG is used to infer motion tendency by modeling the implicit dependency of the current state on priors behaviors, especially the discontinuous motions corresponding to acceleration, deceleration, or turning direction. Moreover, we present a new dataset for vehicle trajectory prediction under traffic lights called VTP-TL. Our experimental results show that our model achieves more than {20.45% and 20.78% }improvement in terms of ADE and FDE, respectively, on VTP-TL as compared to other trajectory prediction algorithms. The dataset and code are available at: https://github.com/VTP-TL/D2-TPred.

Key facts. Cited by 10 papers in the map (data through 14 Oct 2026). Builds on 39 of its 60 references that are in the map. First posted on arXiv 21 Jul 2022.

Builds on

39 of 60 references.

References · 39

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27 more
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  7. 2018Convolutional Social Pooling for Vehicle Trajectory Predictioncited by 221
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  9. 2020Transformer Networks for Trajectory Forecastingcited by 181
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  11. 2019The inD Dataset: A Drone Dataset of Naturalistic Road User Trajectories at German Intersectionscited by 137
  12. 2018TrafficPredict: Trajectory Prediction for Heterogeneous Traffic-Agentscited by 111
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  14. 2018TraPHic: Trajectory Prediction in Dense and Heterogeneous Traffic Using Weighted Interactionscited by 82
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  16. 2021Trajectory Prediction with Latent Belief Energy-Based Modelcited by 60
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Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 1; 2023: 2; 2024: 3; 2025: 2; 2026: 2.

10 papers.

  1. 2022Heterogeneous Trajectory Forecasting via Risk and Scene Graph Learningcited by 11
  2. 2023EPG-MGCN: Ego-Planning Guided Multi-Graph Convolutional Network for Heterogeneous Agent Trajectory Predictioncited by 10
  3. 2024KI-GAN: Knowledge-Informed Generative Adversarial Networks for Enhanced Multi-Vehicle Trajectory Forecasting at Signalized Intersectionscited by 4
  4. 2024Vision Technologies with Applications in Traffic Surveillance Systems: A Holistic Surveycited by 4
  5. 2023Sparse Pedestrian Character Learning for Trajectory Predictioncited by 3
  6. 2024Remember and Recall: Associative-Memory-based Trajectory Predictioncited by 2
  7. 2025Knowledge-Informed Multi-Agent Trajectory Prediction at Signalized Intersections for Infrastructure-to-Everythingcited by 2
  8. 2025V2X-RECT: An Efficient V2X Trajectory Prediction Framework via Redundant Interaction Filtering and Tracking Error Correctioncited by 0
  9. 2026A Generative Model for Closed-Loop Microsimulation of Signalized Intersectionscited by 0
  10. 2026RedLight-VLA: Models for traffic-rule grounding and behavioral emphasis in driving policiescited by 0