5 papers
Explainable Reinforcement Learning for Adaptive Traffic Signal Control
Dickens Kwesiga, Nishu Choudhary, Angshuman Guin +1
Reinforcement Learning (RL) has emerged as a powerful paradigm for adaptive traffic signal control. However, in safety-critical infrastructure like traffic control, the opaque, bla…
Emergency Vehicle Preemption Strategies using Machine Learning to Optimize Traffic Operations
Somdut Roy, Michael Hunter, Abhilasha Saroj +1
Emergency response vehicles (ERVs), such as fire trucks, operate to save lives and mitigate property damage. Emergency vehicle preemption (EVP) is typically implemented to provide…
Evaluating the Robustness of Reinforcement Learning based Adaptive Traffic Signal Control
Dickens Kwesiga, Angshuman Guin, Khaled Abdelghany +1
Reinforcement learning (RL) has attracted increasing interest for adaptive traffic signal control due to its model-free ability to learn control policies directly from interaction…
Adaptive Traffic Signal Control based on Multi-Agent Reinforcement Learning. Case Study on a simulated real-world corridor
Dickness Kakitahi Kwesiga, Angshuman Guin, Michael Hunter
Previous studies that have formulated multi-agent reinforcement learning (RL) algorithms for adaptive traffic signal control have primarily used value-based RL methods. However, re…
Integrating Transit Signal Priority into Multi-Agent Reinforcement Learning based Traffic Signal Control
Dickness Kakitahi Kwesiga, Suyash Chandra Vishnoi, Angshuman Guin +1
This study integrates Transit Signal Priority (TSP) into multi-agent reinforcement learning (MARL) based traffic signal control. The first part of the study develops adaptive signa…