Mohammad Iqbal Khairandish

Intelligent Urban Traffic Management Using Artificial Intelligence and Machine Learning Methods and Algorithms: Challenges and Opportunities

A sustainable and equity-oriented framework for adaptive traffic signal control, in which data from road sensors, traffic cameras, GPS, and public transport systems are integrated with a short-term traffic flow prediction model and a reinforcement learning algorithm, demonstrates that traffic efficiency, environmental sustainability, and transport equity can be integrated within a unified control logic.