wingsweihua / intellilight Goto Github PK
View Code? Open in Web Editor NEWIntelliLight: A Reinforcement Learning Approach for Intelligent Traffic Light Control
IntelliLight: A Reinforcement Learning Approach for Intelligent Traffic Light Control
Warning: Missing yellow phase in tlLogic 'node0', program '0' for tl-index 5 when switching to phase 1
in data/one_run/cross.net.xml in find that only two phases:
<tlLogic id="node0" type="static" programID="0" offset="0"> <phase duration="1000000" state="grrrgGGGgrrrgGGG"/> <phase duration="1000000" state="gGGGgrrrgGGGgrrr"/> </tlLogic>
is there some errors?
Hi author, thanks for your great work.
But I didn't understand about how to compute the duration metric in your code.
In your paper, the duration is defined that "average travel time vehicles spent on approaching lanes (in seconds)".
In your code: you log this value for each step.
travel_time_duration += (traci.simulation.getCurrentTime() / 1000 - vehicle_dict[vehicle_id].first_stop_time)/60.0
But I didn't understand. Please help me to explain that. Thank you so much.
Regards,
Toan
How to visualize results?
Hello! Thanks for your great job! Here are some questions and I hope someone can help me! when runexp.py runs, it often stops at over 600 seconds. And it will automatically pop up another new sumo simulation interface to start over. What can I do to make this experiment run completely?Looking forward to your reply! Thank you so much!
Best regards!
Hello thank you so much for your great work i would like to ask you how can i implement it on real case for example after changing my osm map from open street map to sumo network ?
hello,weihua, thanks for your great job!
In your real-world data experiment, you have 24 intersections, I wonder to know how many agent in this case, 24 or 1 ?
I get the following error while running runexp.py
File "C:\Users\Admin\anaconda3\envs\tf\lib\subprocess.py", line 1207, in _execute_child
startupinfo)
FileNotFoundError: [WinError 2] The system cannot find the file specified
Hello, I'm watching your project. Here are some questions I'm curious about:
According to the runexp.py, it looks like you get your experiment results at the same time of training rather than run the trained model over the same configuration again. Do I misunderstand?
The parameters needed to estimate the reward will fluctuate over time, like queue length, duration. I'm wandering how the performances given in the table 6,7,8,9 are calculated? You adopt the final timestamp's parameter as data? Or you use the average?
Hello,
I'm reading your paper recently. Here are some questions: How do you know if the algorithm will eventually converge? Is there any way to get the corresponding convergence curve based on the generated data file? Thanks.
It seems like u modify the paper,and the code do not match what propose from the paper.
Looking forward to the new code committed.
For Errors like
ImportError: No module named traci
Hello, thank you for your public code. Is there test data to reproduce the result in your paper?
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