Training and Application Code of the MDP Driving Policy in Highway
收藏ETS-Data2023-08-07 更新2026-02-07 收录
下载链接：
https://doi.org/10.26599/ETSD.2023.9190018
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资源简介：
The dataset comes from the paper "Markov probabilistic decision making of self-driving cars in a highway with random traffic flow: a simulation study" and mainly consists of three parts:
1. The "policy_training" folder, which includes the code used for training driving strategies in the highway scenario mentioned in the paper. The main function is "main_v3.cpp," and the functionality is implemented in the file "f_define_v3.cpp." Additionally, "to_strategy.m" exports the trained strategy as a state-action table for application, and "FIGURE.me" visualizes this table.
2. The "policy_application" folder contains "test.py" as the main file, which uses "MdpModel.py" to call the state-action table from the "Strategy" folder and visualizes it through "MdpModel.py." The "Map" and "Vehicle" folders store visualization elements.
3. The third part is a video of the visualization results named "simulation_demo.avi."
