Y Han, M Wang, L Leclercq - Communications in Transportation Research, 2023 - Elsevier
In recent years, the advancement of artificial intelligence techniques has led to significant interest in reinforcement learning (RL) within the traffic and transportation community …
Deep reinforcement learning (DRL) has empowered a variety of artificial intelligence fields, including pattern recognition, robotics, recommendation systems, and gaming. Similarly …
Traffic congestion is a major concern for many metropolises. Although it is difficult to regulate traffic flow because of numerous complexities and uncertainties, the traffic congestion …
In urban areas, the problem of recurring daily congestion is constantly increasing. A possible solution is seen in the application of adaptive traffic signal control (ATSC) systems for the …
L Da, M Gao, H Mei, H Wei - Proceedings of the AAAI Conference on …, 2024 - ojs.aaai.org
Numerous methods are proposed for the Traffic Signal Control (TSC) tasks aiming to provide efficient transportation and mitigate congestion waste. In recent, promising results have …
Emergency vehicles (EMVs) play a crucial role in responding to time-critical calls such as medical emergencies and fire outbreaks in urban areas. Existing methods for EMV dispatch …
L Da, M Gao, H Mei, H Wei - arXiv preprint arXiv:2308.14284, 2023 - researchgate.net
Numerous solutions are proposed for the Traffic Signal Control (TSC) tasks aiming to provide efficient transportation and mitigate congestion waste. Recently, promising results …
Managing the mixed traffic involving connected and autonomous vehicles (CAVs) and human-driven vehicles (HVs) at a signalized intersection has become a concern of …
The widespread penetration of inverter-based resources has profoundly impacted the electrical stability of power systems (PSs). Deepening grid integration of photovoltaic and …