DayuanTan / PALM_public

Code for paper "PALM: Platoons Based Adaptive Traffic Light Control System for Mixed Vehicular Traffic".

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PALM: Platoons Based Adaptive Traffic Light Control System for Mixed Vehicular Traffic

This repo hosts the code for paper "PALM: Platoons Based Adaptive Traffic Light Control System for Mixed Vehicular Traffic".

Welcome to cite our paper! Your citation is the best encourage for young scholar like us.

To cite:

Pre-requisites

  1. You need know how to use SUMO.

    You may find my tutorial is helpful for beginners. I suggest you go over it before you continue.

  2. You are suggested to read our paper to understand the algorithms. Our paper includes 3 algorithms. The static TL and ATL are easy to understand. Our PALM may be a little complex.

Code

This code includes our implementations of those 3 algorithms:

  • Static Traffic Light Control System
  • Actuated Traffic Light Control System
  • PALM

and detialed steps and explanations.

To see the code, please read this Readme.

Code Completeness

  • Static Traffic Light Control System: 100%
    • You should be able to run it successfully.
  • Actuated Traffic Light Control System: 100%
    • You should be able to run it successfully.
  • PALM: 99%.
    • My laptop was broken. The code I stored on cloud doesn't have the newest version. But it is super close to the newest version. I lost about 2 or 3 days updates.
    • I thought about fixing it. But the priority of this fix task is low.
    • I cannot gurantee you can run it. But the code are still very valuabble, especially I provide the very detialed steps and explanations of my code. It's enough for you to understand how to implement it and develop your algorithm.

Questions

I'd love to answer any questions. Feel free to post an issue to email me.

Our other open source research

https://dayuantan.github.io/AboutMe/researches.html

About

Code for paper "PALM: Platoons Based Adaptive Traffic Light Control System for Mixed Vehicular Traffic".

License:GNU General Public License v3.0


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Language:Python 100.0%