Guiling 'Grace' Wang Wins IEEE Vehicular Technology Society 2023 Best Paper Award

IEEE Fellow Guiling “Grace” Wang, distinguished professor, associate dean for research, and founding director of the AI Center for Research in the Ying Wu College of Computing (YWCC), has been awarded the IEEE Vehicular Technology Society 2023 Best Land Transportation Paper Award. This accolade, received four years after publication of her influential paper, “A Deep Reinforcement Learning Network for Traffic Light Cycle Control,” recognizes its significant research impact and high citation.

Wang's prestigious award is a testament to her pioneering work in the field of Artificial Intelligence and its application in urban traffic management. Sharing this recognition are her former PhD students Xiaoyuan Liang Ph.D. ’19, recipient of the YWCC 2020 Thesis Award; Xunsheng Du, a data analyst at Chevron; and Zhu Han, Moores professor at the University of Houston.

The award ceremony, held at the VTC2023-Fall Conference in Hong Kong, saw Dr. Xiaoyuan Liang, a proud YWCC alumnus, in attendance to receive the official certification. This marks yet another instance of YWCC's recognition in the highly competitive society level best paper awards, underlining the college's leading role in innovative research.

The awarded paper, first published in 2019, made significant strides in AI research by developing a deep reinforcement learning model to intelligently control traffic lights. Its aim was to dynamically adjust cycle durations and reduce energy consumption, a goal achieved by analyzing real-time traffic data and dividing intersections into smaller, more manageable grids. This approach, integrating multiple optimization elements, has proven highly effective in improving traffic light control efficiency.

Building on this success, Wang’s group recently published “SafeLight: A Reinforcement Learning Method toward Collision-free Traffic Signal Control” in AAAI, a premier AI conference. This paper takes the innovation further by incorporating safety considerations into intersection control, optimizing both efficiency and safety - a first in the field. Currently, Wang’s team is expanding their research to AI-based control of multiple intersections, showcasing their continued commitment to advancing urban traffic management through AI.

The recognition of Wang's work by the IEEE Vehicular Technology Society is not only a personal achievement but also a milestone in the application of AI to real-world challenges. Her research is paving the way for safer, more efficient cities, and stands as a beacon of innovation and excellence in the field of artificial intelligence.