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Esa Apriaskar on Muck Rack

Esa Apriaskar

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Articles

Deep reinforcement learning-based traffic signal control in multi-intersection environments: a comparative study of DQN variants

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By Muhammad Maulana, Dimas Ilham, Dhidik Prastiyanto, Akhyar Abdillah Manaf, Rasyid Muhammad Nurhakim, Esa Apriaskar
| Nature Verified
Abstract Traffic congestion at urban intersections is commonly associated with non-adaptive Fixed Time Signal Control (FTSC), which cannot respond effectively to variations in vehicle types, traffic demand, and intersection policies. Although deep reinforcement learning (DRL) has been increasingly applied to traffic signal control, comprehensive evaluations under multi-intersection environments with heterogeneous vehicles and different turning policies remain limited.
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