OPTIMIZED URBAN TRAFFIC CONTROL WITH ADAPTIVE EXPONENTIAL REWARD DEEP Q NETWORK AT INTERSECTION USING PARTICLE SWARM OPTIMIZATION
The excessive number of vehicles on a road network causes congestion. Dynamic traffic conditions result in the need for a traffic control system that can adapt to these conditions. Indonesia is actively developing an Artificial Intelligence-based traffic control system. A Reinforcement Learning-base...
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| Format: | Final Project |
| Language: | Indonesia |
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| Online Access: | https://digilib.itb.ac.id/gdl/view/75412 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |