This is the source codes and modeling data for paper: LSTM + Transformer Real-Time Crash Risk Evaluation Using Traffic Flow and Risky Driving Behavior Data
The codes are running in python 3.10.13. The LSTM and Transformer models are built using Tensorflow (2.10.1) The other baseline models (i.e., Logistic Regreesion, Support vector Machine, and XGBoost) are built using scikit-learn (1.3.0) The data processed for model training and testing includes: (1) Traffic flow data, (2) Risky driving behavior data, (3) Crash index data, and (4) Aggregated traffic flow and risky driving behavior data. Due to the data privacy, the raw data cannot be open to public. Please feel free to contact the authors if you have any questions or issues.
This is the paper link: https://ieeexplore.ieee.org/abstract/document/10633785/.
@article{han2024lstm, title={LSTM $+ $ Transformer Real-Time Crash Risk Evaluation Using Traffic Flow and Risky Driving Behavior Data}, author={Han, Lei and Abdel-Aty, Mohamed and Yu, Rongjie and Wang, Chenzhu}, journal={IEEE Transactions on Intelligent Transportation Systems}, year={2024}, publisher={IEEE} }