Evaluating Autonomous Systems Before Deployment

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Autonomous systems must operate safely in complex human environments, but real-world testing is limited and risky. We develop scalable evaluation methods — including generative simulation for interactive environments, diffusion models for trajectory prediction and scenario generation, and off-policy evaluation techniques — to rigorously assess autonomous system performance before deployment. We also build benchmarks and datasets for driving reasoning to enable standardized evaluation across the community.

Selected Publications

2026

  1. arXiv
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    SCAPE: Scenario-Conditioned Simulation-Augmented Policy Evaluation
    Dijie Zhu, Seunghun Oh, Ruopeng Huang, and 3 more authors
    arXiv preprint (coming soon), 2026

2025

  1. ICML 2025
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    WOMD-Reasoning: A Large-Scale Language Dataset for Interactions and Driving Intentions Reasoning
    Yiheng Li, Cunxin Fan, Chongjian Ge, and 9 more authors
    Forty-Second International Conference on Machine Learning (ICML), 2025
  2. CoRL 2025
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    SocialNav-SUB: Benchmarking VLMs for Scene Understanding in Social Robot Navigation
    Michael J. Munje, Chen Tang, Shuijing Liu, and 6 more authors
    Conference on Robot Learning (CoRL), 2025

2024

  1. ECCV 2024
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    Optimizing Diffusion Models for Joint Trajectory Prediction and Controllable Generation
    Yixiao Wang, Chen Tang, Lingfeng Sun, and 8 more authors
    In European Conference on Computer Vision (ECCV), 2024

2023

  1. RA-L 2023
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    Editing Driver Character: Socially-Controllable Behavior Generation for Interactive Traffic Simulation
    Wei-Jer Chang*, Chen Tang*, Chenran Li, and 3 more authors
    IEEE Robotics and Automation Letters (RA-L), 2023
    presented at 2023 CVPR Workshop on Multi-Agent Behavior: Properties, Computation, and Emergence (MABe) and 2024 IEEE International Conference on Robotics and Automation (ICRA)

2021

  1. NeurIPS 2021
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    Exploring Social Posterior Collapse in Variational Autoencoder for Interaction Modeling
    Chen Tang, Wei Zhan, and Masayoshi Tomizuka
    In Advances in Neural Information Processing Systems (NeurIPS), 2021