Deep reinforcement learning for traffic light timing optimization

HIGHLIGHTS

• who: Bin Wang and collaborators from the School of Computer Science and Engineering, Central South University, Changsha, China have published the paper: Deep Reinforcement Learning for Traffic Light Timing Optimization, in the : Processes 2022, 10, 2458. of /2022/
• what: The authors propose the EP-D3QN algorithm based on MP, SOTL, and 3DQN algorithms. To verify the performance of EP-D3QN, the authors compare it with the following methods..
• how: This paper proposes a traffic light timing optimization method based on double dueling deep Q-network MaxPressure and Self-organizing traffic lights (SOTL) namely . . .
  

   

  

  If you want to have access to all the content you need to log in!

  Thanks :)

  Username or Email

  Password

  Remember me

  Lost your password?

  If you don't have an account, you can create one here.