Deep Reinforcement Learning for Traffic Light Optimization

COŞKUN M., Baggag A., Chawla S.

2018 IEEE International Conference on Data Mining Workshops (ICDMW), Singapore, Singapore, Singapur, 17 - 20 Kasım 2018 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/icdmw.2018.00088
  • Basıldığı Şehir: Singapore, Singapore
  • Basıldığı Ülke: Singapur
  • Anahtar Kelimeler: Deep Q-Learning, Deep Policy Gradient, Traffic Light Optimization, NETWORKS
  • Ankara Üniversitesi Adresli: Evet

Özet

Deep Reinforcement Learning has the potential of practically addressing one of the most pressing problems in road traffic management, namely that of traffic light optimization (TLO). The objective of the TLO problem is to set the timings (phase and duration) of traffic lights in order to minimize the overall travel time of the vehicles that traverse the road network.