This is the official code of the paper "Continual Interactive Behavior Learning With Scenarios Divergence Measurement: A Dynamic Gradient Scenario Memory Approach",Yunlong Lin, Zirui Li, Cheng Gong, Chao Lu, Xinwei Wang, Jianwei Gong. The paper is submitted to IEEE Transanctions on Intelligent Transportation Systems.
Codes are implemented in Ubuntu 18.04. The detailed requirement of setup is shown in requirement.txt. You can have everything set up by running:
pip install -r requirements.txt
Dataset used in this paper is the publicly available INTERACTION Dataset: An INTERnational, Adversarial and Cooperative moTION Dataset in Interactive Driving Scenarios with Semantic Maps. Subsets denoted as MA, FT, ZS, EP, SR are used in experiments to construct continuous scenarios. INTERACTION
The proposed approach is plug-and-play. As an example, the Social-STGCNN model proposed in paper Social-STGCNN: A Social Spatio-Temporal Graph Convolutional Neural Network for Human Trajectory Prediction is adopted as base model in this work. The original base model is availble in base model.