ADAPTIVE Q-LEARNING FOR SUSTAINABLE ELECTRIC VEHICLE ADAPTIVE CRUISE CONTROL IN THAILAND'S SMART TOURISM
DOI:
https://doi.org/10.14456/aisr.2025.13Keywords:
Adaptive Cruise Control (ACC), Electric Vehicles (EVs), Adaptive Q-Learning, Thailand, SustainabilityAbstract
This study explores the integration of adaptive Q-learning into Electric Vehicle (EV) Adaptive Cruise Control (ACC) systems, with a focus on enhancing sustainability in Thailand's smart tourism destinations. It presents an adaptive Q-learning approach to improve efficiency, safety, and environmental performance in dynamic environments by learning optimal speed and distance policies through continuous interaction. The simulations demonstrated that adaptive Q-learning significantly improved ACC's fuel efficiency, reduces traffic congestion and improves air quality. These improvements are crucial for developing sustainable transportation solutions in environmentally sensitive tourist destinations. The study stresses how adaptive Q-learning transforms EV safety, efficiency, and environmental management, setting a sustainable benchmark for ADAS systems in Thailand and elsewhere.
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