Assoc. Prof. Dr. Bing Li | Traffic Engineering | Best Researcher Award

Kunming University of Science and Technology, China.

Bing Li is an Associate Professor at Kunming University of Science and Technology, specializing in intelligent transportation systems, traffic management and control, and big data mining. After completing his M.S. and Ph.D. degrees from Kunming University of Science and Technology in 2015 and 2019, respectively, he has focused on advancing smart transportation technologies. With more than 20 published articles in prominent journals, his work has contributed significantly to the development of traffic management solutions in China, specifically in Yunnan Province. He actively collaborates on government projects aimed at enhancing transportation infrastructure and urban mobility.

Profile

Scopus

Education ๐ŸŽ“

Bing Li completed his M.S. and Ph.D. at Kunming University of Science and Technology, Kunming, China, in 2015 and 2019, respectively. His academic background laid the foundation for his in-depth research in intelligent transportation systems and big data applications in traffic control.

Experience ๐Ÿ’ผ

Currently, Bing Li serves as an Associate Professor at the Faculty of Transportation Engineering at Kunming University of Science and Technology. He has contributed significantly to over 30 transportation planning and intelligent transportation projects across China. Li has also led research initiatives focused on the integration of big data in traffic management and control, driving advancements in this vital sector.

Research Interests ๐Ÿ”

Intelligent Transportation Systems (ITS)
Bing Liโ€™s research is deeply rooted in the development of intelligent transportation systems (ITS), which aim to integrate advanced technology into traffic management and control. By utilizing ITS, he works on creating systems that monitor, analyze, and manage traffic in real-time to improve urban mobility.

Traffic Management and Control
A key focus of his work is optimizing traffic management and control strategies. Through innovative techniques, he seeks to reduce congestion, improve traffic flow, and minimize delays at intersections, contributing to a smoother transportation experience for urban commuters.

Big Data Mining in Transportation
Bing Li applies big data mining to traffic management, where vast amounts of data from various sources are processed and analyzed to identify patterns, predict traffic trends, and inform decision-making. His work leverages this data to implement solutions that enhance the efficiency and safety of transportation systems.

Urban Traffic Flow Optimization
One of his major research goals is to optimize urban traffic flows. By studying traffic patterns, he aims to develop models and systems that reduce congestion, enhance road safety, and improve the overall performance of transportation networks in busy urban environments.

Smart Systems for Real-Time Traffic Data
Bing Liโ€™s work also explores the development of smart systems that facilitate real-time traffic data analysis. These systems enable immediate responses to changing traffic conditions, contributing to safer and more efficient traffic management strategies, especially in urban areas.

Selected Publications ๐Ÿ“š

An Evaluation System for Signalized Intersections in a Mixed-Traffic Environment
Li, B., Gao, J., Yin, J., He, X., Yang, J.
Published in Transportation Planning and Technology, 2024, 47(5), pp. 681โ€“708.
Cited by: 1 citation

Urban Road Travel Speed Prediction Based on Multi-Feature Data Fusion
Huo, J., Cheng, W., Li, B.
Published in Shenzhen Daxue Xuebao (Ligong Ban)/Journal of Shenzhen University Science and Engineering, 2023, 40(2), pp. 195โ€“202.
Cited by: 1 citation

Evaluation Model of Traffic Organization for Left-turn Prohibition Based on Macroscopic Fundamental Diagram
Li, B., Yang, H.-Y., Zheng, Z.-X., Feng, Y., Wang, Z.-H.
Published in Jiaotong Yunshu Xitong Gongcheng Yu Xinxi/Journal of Transportation Systems Engineering and Information Technology, 2022, 22(3), pp. 179โ€“189.
Cited by: 2 citations

Capacity and Delay of Right-turn Vehicles at Signalized Intersections Under Influence of Pedestrian Two-stage Crossing
Li, B., Wang, Z.-H., Ma, M.-W., Yang, H.-Y., Feng, Y.
Published in Jiaotong Yunshu Xitong Gongcheng Yu Xinxi/Journal of Transportation Systems Engineering and Information Technology, 2022, 22(2), pp. 257โ€“267.
Cited by: 6 citations

Capacity Estimation of Advance Right-Turn Motor Vehicles Considering Nonstrict Priority Crossing Behaviors under Mixed-Traffic Conditions
Li, B., Yang, H., Cheng, W., Ma, M.
Published in Journal of Transportation Engineering Part A: Systems, 2022, 148(2), 04021114.

 

 

Assoc. Prof. Dr. Bing Li | Traffic Engineering | Best Researcher Award