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ControlTraj: Controllable Trajectory Generation with Topology-Constrained Diffusion Model

Published 23 Apr 2024 in cs.LG and cs.AI | (2404.15380v1)

Abstract: Generating trajectory data is among promising solutions to addressing privacy concerns, collection costs, and proprietary restrictions usually associated with human mobility analyses. However, existing trajectory generation methods are still in their infancy due to the inherent diversity and unpredictability of human activities, grappling with issues such as fidelity, flexibility, and generalizability. To overcome these obstacles, we propose ControlTraj, a Controllable Trajectory generation framework with the topology-constrained diffusion model. Distinct from prior approaches, ControlTraj utilizes a diffusion model to generate high-fidelity trajectories while integrating the structural constraints of road network topology to guide the geographical outcomes. Specifically, we develop a novel road segment autoencoder to extract fine-grained road segment embedding. The encoded features, along with trip attributes, are subsequently merged into the proposed geographic denoising UNet architecture, named GeoUNet, to synthesize geographic trajectories from white noise. Through experimentation across three real-world data settings, ControlTraj demonstrates its ability to produce human-directed, high-fidelity trajectory generation with adaptability to unexplored geographical contexts.

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References (55)
  1. Human mobility: Models and applications. Physics Reports 734 (2018), 1–74.
  2. Chu Cao and Mo Li. 2021. Generating Mobility Trajectories with Retained Data Utility. In Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining. 2610–2620.
  3. Deep Learning for Trajectory Data Management and Mining: A Survey and Beyond. arXiv preprint arXiv:2403.14151 (2024).
  4. Wide & deep learning for recommender systems. In Proceedings of the 1st workshop on deep learning for recommender systems. 7–10.
  5. Personalized route recommendation using big trajectory data. In 2015 IEEE 31st international conference on data engineering. IEEE, 543–554.
  6. Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805 (2018).
  7. Prafulla Dhariwal and Alexander Nichol. 2021. Diffusion models beat gans on image synthesis. Advances in Neural Information Processing Systems 34 (2021), 8780–8794.
  8. An image is worth 16x16 words: Transformers for image recognition at scale. arXiv preprint arXiv:2010.11929 (2020).
  9. LDPTrace: Locally Differentially Private Trajectory Synthesis. arXiv preprint arXiv:2302.06180 (2023).
  10. Dragoon: a hybrid and efficient big trajectory management system for offline and online analytics. The VLDB Journal 30 (2021), 287–310.
  11. Learning to simulate human mobility. In Proceedings of the 26th ACM SIGKDD international conference on knowledge discovery & data mining. 3426–3433.
  12. Generative Adversarial Nets. In Advances in Neural Information Processing Systems, Vol. 27.
  13. Learning to route with sparse trajectory sets. In 2018 IEEE 34th International Conference on Data Engineering (ICDE). IEEE, 1073–1084.
  14. Attention based spatial-temporal graph convolutional networks for traffic flow forecasting. In Proceedings of the AAAI conference on artificial intelligence, Vol. 33. 922–929.
  15. Masked autoencoders are scalable vision learners. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition. 16000–16009.
  16. Condtraj-gan: Conditional sequential gan for generating synthetic vehicle trajectories. In Pacific-Asia Conference on Knowledge Discovery and Data Mining. Springer, 79–91.
  17. Denoising diffusion probabilistic models. Advances in Neural Information Processing Systems 33 (2020), 6840–6851.
  18. Towards Unifying Diffusion Models for Probabilistic Spatio-Temporal Graph Learning. arXiv preprint arXiv:2310.17360 (2023).
  19. Christian S Jensen. 2022. Digitalization in the Service of Society: The Case of Big Vehicle Trajectory Data. In Proceedings of the 34th International Conference on Scientific and Statistical Database Management. 1–1.
  20. DiffWave: A Versatile Diffusion Model for Audio Synthesis. In International Conference on Learning Representations.
  21. Diffusion convolutional recurrent neural network: Data-driven traffic forecasting. arXiv preprint arXiv:1707.01926 (2017).
  22. Modeling Trajectories with Neural Ordinary Differential Equations. In IJCAI. 1498–1504.
  23. Foundation Models for Time Series Analysis: A Tutorial and Survey. arXiv preprint arXiv:2403.14735 (2024).
  24. A survey on deep learning for human mobility. ACM Computing Surveys (CSUR) 55, 1 (2021), 1–44.
  25. Glide: Towards photorealistic image generation and editing with text-guided diffusion models. arXiv preprint arXiv:2112.10741 (2021).
  26. OpenStreetMap contributors. 2017. Planet dump retrieved from https://planet.osm.org . https://www.openstreetmap.org.
  27. A non-parametric generative model for human trajectories. In IJCAI, Vol. 18. 3812–3817.
  28. Learning transferable visual models from natural language supervision. In International conference on machine learning. PMLR, 8748–8763.
  29. LSTM-TrajGAN: A Deep Learning Approach to Trajectory Privacy Protection. In 11th International Conference on Geographic Information Science (GIScience 2021).
  30. High-resolution image synthesis with latent diffusion models. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 10684–10695.
  31. U-net: Convolutional networks for biomedical image segmentation. In International Conference on Medical image computing and computer-assisted intervention. Springer, 234–241.
  32. Learning to generate maps from trajectories. In Proceedings of the AAAI conference on artificial intelligence, Vol. 34. 890–897.
  33. A deep gravity model for mobility flows generation. Nature communications 12, 1 (2021), 6576.
  34. Deep unsupervised learning using nonequilibrium thermodynamics. In International Conference on Machine Learning. PMLR, 2256–2265.
  35. Denoising diffusion implicit models. arXiv preprint arXiv:2010.02502 (2020).
  36. Attention is all you need. Advances in neural information processing systems 30 (2017).
  37. A survey on trajectory data management, analytics, and learning. ACM Computing Surveys (CSUR) 54, 2 (2021), 1–36.
  38. Large scale GPS trajectory generation using map based on two stage GAN. Journal of Data Science 19, 1 (2021), 126–141.
  39. Learning to Estimate the Travel Time. In Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. Association for Computing Machinery, London, United Kingdom, 858–866.
  40. Trajectory simplification with reinforcement learning. In 2021 IEEE 37th International Conference on Data Engineering (ICDE). IEEE, 684–695.
  41. DiffSTG: Probabilistic Spatio-Temporal Graph Forecasting with Denoising Diffusion Models. arXiv preprint arXiv:2301.13629 (2023).
  42. Connecting the dots: Multivariate time series forecasting with graph neural networks. In Proceedings of the 26th ACM SIGKDD international conference on knowledge discovery & data mining. 753–763.
  43. Graph Wavenet for Deep Spatial-Temporal Graph Modeling. In Proceedings of the 28th International Joint Conference on Artificial Intelligence (Macao, China) (IJCAI’19). 1907–1913.
  44. trajGANs: using generative adversarial networks for geo-privacy protection of trajectory data. Vision paper (2018).
  45. DeepRailway: A Deep Learning System for Forecasting Railway Traffic. In 2018 IEEE Conference on Multimedia Information Processing and Retrieval (MIPR). 51–56.
  46. Simulating continuous-time human mobility trajectories. In Proc. 9th Int. Conf. Learn. Represent. 1–9.
  47. MetaPTP: an adaptive meta-optimized model for personalized spatial trajectory prediction. In Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. 2151–2159.
  48. Diffusion models: A comprehensive survey of methods and applications. arXiv preprint arXiv:2209.00796 (2022).
  49. Activity Trajectory Generation via Modeling Spatiotemporal Dynamics. In Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. 4752–4762.
  50. Paul A Zandbergen. 2014. Ensuring confidentiality of geocoded health data: assessing geographic masking strategies for individual-level data. Advances in medicine 2014 (2014).
  51. DP-TrajGAN: A privacy-aware trajectory generation model with differential privacy. Future Generation Computer Systems (2022).
  52. Yu Zheng. 2015. Trajectory data mining: an overview. ACM Transactions on Intelligent Systems and Technology (TIST) 6, 3 (2015), 1–41.
  53. Urban computing: concepts, methodologies, and applications. ACM Transactions on Intelligent Systems and Technology (TIST) 5, 3 (2014), 1–55.
  54. Semi-supervised federated learning for travel mode identification from gps trajectories. IEEE Transactions on Intelligent Transportation Systems 23, 3 (2021), 2380–2391.
  55. DiffTraj: Generating GPS Trajectory with Diffusion Probabilistic Model. In Thirty-seventh Conference on Neural Information Processing Systems.
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