Li Shiwei is an accomplished Associate Professor and the Director of the Scientific Research Office at Lanzhou Jiaotong University. With a PhD in Transportation Planning and Management, Li is a leading research scholar in the field of transportation systems, artificial intelligence, and data mining. His academic career is marked by significant contributions to both teaching and research, positioning him as a key figure in the development of intelligent transportation solutions.
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ORCID Profile
Li Shiwei has published over 30 academic papers, contributing extensively to the field of transportation and intelligent systems. His work has been recognized with more than 20 academic awards, highlighting his influence and the high regard in which his peers hold his research. Additionally, Li has edited one monograph, further demonstrating his expertise and commitment to advancing knowledge in his discipline.
Education
Li Shiwei received his PhD in Transportation Planning and Management from Lanzhou Jiaotong University in April 2020. Prior to this, he earned a Master’s degree in Management Science and Engineering from Southwest Jiaotong University in January 2006, and a Bachelor’s degree in Information Management and Information Systems from Northwest Normal University in June 2003. This solid educational foundation underpins his research and teaching excellence.
Research Focus
Li Shiwei’s research directions encompass comprehensive transportation informatization, intelligent transportation systems, complex system analysis and optimization, autonomous driving, artificial intelligence, and traffic big data mining. His work aims to address contemporary challenges in transportation through the integration of advanced technologies and data-driven approaches.
Professional Journey
Throughout his career, Li Shiwei has held key academic and administrative positions. As an Associate Professor and Director of the Scientific Research Office at Lanzhou Jiaotong University, he has played a pivotal role in guiding research initiatives and fostering academic excellence. His professional journey is characterized by a commitment to innovation and the development of cutting-edge transportation solutions.
Honors & Awards
Li Shiwei has been the recipient of more than 20 academic awards, reflecting his outstanding contributions to research and academia. These accolades underscore his expertise and the impact of his work on the field of transportation and intelligent systems.
Publications Noted & Contributions
With over 30 academic papers published, Li Shiwei has made significant contributions to the body of knowledge in his field. His publications address critical issues in transportation and intelligent systems, offering new insights and proposing innovative solutions. Additionally, he has edited one monograph, further establishing his authority and thought leadership in the discipline.
A Road Data Assets Revenue Allocation Model Based on a Modified Shapley Value Approach Considering Contribution Evaluation
Journal: Scientific Reports
Publication Date: 2024-03-02
DOI: 10.1038/s41598-024-55819-7
ISSN: 2045-2322
Contributors: Shiwei Li, Lei Chu, Jisen Wang, Yuzhao Zhang
This article introduces a novel revenue allocation model for road data assets, which is based on a modified Shapley value approach. The model incorporates a thorough evaluation of each contributor’s input to ensure a fair and balanced distribution of revenue among stakeholders. This method enhances traditional allocation models by providing a more accurate reflection of individual contributions to the overall asset value.
Simulation of Cross-Pedestrian Flow in Intersection Based on Direction Fuzzy Visual Field
Journal: IET Intelligent Transport Systems
Publication Date: 2024-01-31
DOI: 10.1049/itr2.12486
Contributors: Shiwei Li, Qianqian Li, Jiao Xu, Yuzhao Zhang
This study presents a simulation model for cross-pedestrian flow at intersections, utilizing a direction fuzzy visual field approach. The research aims to improve the understanding of pedestrian behavior in complex traffic environments, providing insights that could enhance traffic management and pedestrian safety measures.
Simulation of Bi-directional Pedestrian Flow in Corridor Based on Direction Fuzzy Visual Field
Journal: Scientific Reports
Publication Date: 2023-11-07
DOI: 10.1038/s41598-023-46530-0
ISSN: 2045-2322
Contributors: Shiwei Li, Qianqian Li, Ganglong Zhong, Yuzhao Zhang
In this article, the authors develop a simulation model to analyze bi-directional pedestrian flow in corridors, using a direction fuzzy visual field. The study aims to provide a deeper understanding of pedestrian dynamics in confined spaces, which can inform the design of more efficient and safer public infrastructures.
Simulation Study on Pedestrian Strategy Choice Based on Direction Fuzzy Visual Field
Journal: Journal of Ambient Intelligence and Humanized Computing
Publication Date: 2020-02-09
DOI: 10.1007/s12652-019-01389-w
Contributors: Shi-wei Li, Jian-qiang Wang, Yu-zhao Zhang
This research investigates pedestrian strategy choices using a direction fuzzy visual field approach. The simulation study provides insights into how pedestrians make navigational decisions, which can be applied to improve pedestrian flow management and urban planning.
Impact of Personalised Route Recommendation in the Cooperation Vehicle-Infrastructure Systems on the Network Traffic Flow Evolution
Journal: Journal of Simulation
Publication Date: 2019-10-02
DOI: 10.1080/17477778.2018.1515579
ISSN: 1747-7778, 1747-7786
Contributors: Jianqiang Wang, Wenjuan Zhou, Shiwei Li, Danlei Shan
This article explores the effects of personalized route recommendations in cooperative vehicle-infrastructure systems on the evolution of network traffic flow. The study highlights how tailored route suggestions can optimize traffic distribution, reduce congestion, and enhance overall traffic efficiency.
Research Timeline
Li Shiwei’s research career has seen him lead or participate in the completion of over 60 projects. These projects span various prestigious foundations and collaborative initiatives, including the National Natural Science Foundation, the National Humanities and Social Science Foundation, and the Ministry of Education Industry-Education Integration Project. His research timeline is marked by continuous engagement with complex and impactful studies.
Collaborations and Projects
Li Shiwei has been involved in numerous collaborative projects, working with both academic institutions and industry partners. Notable collaborations include the Tianjin University-Lanzhou Jiaotong University Independent Innovation Fund Cooperation Project and the School-Enterprise Cooperation Project. His ability to bridge academia and industry has facilitated the successful implementation of innovative research projects.
Teaching Work
Li Shiwei is dedicated to educating the next generation of professionals in his field. He teaches master’s courses such as “Artificial Intelligence and Applications” and “Transportation and Logistics Data Analysis and Mining,” as well as undergraduate courses including “Principles of Management,” “Information Economics,” “Enterprise Resource Planning,” “Organizational Behavior,” and “Production Operation Management.” His teaching work reflects his broad expertise and commitment to academic excellence.