Dr. Licheng Zhang | Energy – Senior Engineer at Chang’an University, China.
Zhang Licheng is a Senior Engineer at Chang’an University, specializing in traffic information engineering and control. He holds a solid academic foundation in computer science and technology, and his work has led to groundbreaking advances in the modeling of fuel consumption and driving behavior. Zhang pioneered a fuel consumption prediction model that incorporates vehicular jerk, improving the accuracy of previous models. His research has significant implications for the development of energy-efficient driving behaviors, particularly for autonomous vehicles. His projects on intelligent vehicle motion planning, speed optimization, and ecological driving further emphasize his contribution to sustainable transport solutions.
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Education
🎓Zhang Licheng completed his undergraduate degree in computer science and technology, followed by a master’s and doctoral degree in traffic information engineering and control. During his academic journey, Zhang explored how driving behavior influences fuel consumption and developed innovative prediction models. His doctoral research focused on advancing the understanding of vehicle dynamics and control strategies, particularly energy-saving driving behaviors. Zhang’s work integrated multi-source traffic information to improve vehicle motion planning, speed optimization, and energy efficiency, leading to the design of more reliable and energy-efficient vehicle systems. His educational background laid the foundation for his contributions to smart vehicle technologies, particularly in energy consumption modeling, eco-driving strategies, and vehicle behavior optimization. Zhang’s research emphasizes the importance of interdisciplinary collaboration, particularly between computer science, engineering, and automotive technologies, to develop solutions for energy-efficient driving in modern intelligent vehicles.
Experience
Zhang Licheng is a Senior Engineer at Chang’an University, where he works on developing and optimizing energy-efficient driving behaviors for intelligent vehicles. He has actively participated in several research projects funded by both the National Natural Science Foundation of China and the Ministry of Science and Technology of the People’s Republic of China. Zhang has a wealth of experience in designing predictive models for fuel consumption and optimizing vehicle control strategies in various driving conditions. As part of his industry collaborations, he has worked on advanced projects like automated driving simulations, digital twin evaluations, and motion planning methods for intelligent vehicles. Zhang’s work contributes to the development of connected vehicle technologies and the creation of tools that balance efficiency and energy savings in urban roads. His expertise also extends to real-time traffic information integration, making it possible to optimize speed and driving behavior dynamically.
Research Interests
🔬Zhang Licheng’s primary research focus is on the relationship between driving behavior and fuel consumption, particularly in the context of intelligent and connected vehicles. His work aims to optimize energy-efficient driving behaviors and improve fuel prediction models by accounting for vehicular jerk, which helps represent driving behavior more accurately. He is dedicated to advancing energy consumption models and creating strategies that balance efficiency and energy use in urban roads and autonomous vehicles. Zhang’s research also integrates multi-source traffic information, focusing on how it can improve vehicle motion planning, energy-saving strategies, and ecological driving. Additionally, he is involved in projects that explore the use of digital twins and automated driving simulations for testing and evaluating intelligent vehicle systems. Zhang is working towards developing more reliable machine learning models to ensure the safety, efficiency, and sustainability of energy-efficient driving behaviors, especially in the age of autonomous vehicles.
Awards
🏆Zhang Licheng has received multiple honors for his research contributions in traffic engineering and intelligent vehicle technologies. Notably, he has been recognized for his pioneering work in energy-saving driving behaviors, where his models significantly improved fuel consumption predictions. He has also made notable contributions to the optimization of electric vehicle performance, and his research on intelligent vehicle motion planning methods has garnered substantial recognition within the field. Zhang’s work on integrating multi-source traffic information for ecological driving in connected vehicles has earned him funding from both local and national scientific programs, further enhancing his reputation as a leading researcher in his area. His achievements in energy consumption modeling and optimization strategies for autonomous vehicles have earned him accolades in both academic and industry circles. Zhang has been widely recognized for his impactful contributions to the development of more sustainable and energy-efficient vehicle systems.
Publications
New innovations in pavement materials and engineering: A review on pavement engineering research
Authors: JE Office, J Chen, H Dan, Y Ding, Y Gao, M Guo, S Guo, B Han, B Hong, …
Citations: 151
Year: 2021
Improved watershed analysis for segmenting contacting particles of coarse granular soils in volumetric images
Authors: Q Sun, J Zheng, C Li
Citations: 60
Year: 2019
Highway constructions on the Qinghai-Tibet Plateau: Challenge, research and practice
Authors: A Sha, B Ma, H Wang, L Hu, X Mao, X Zhi, H Chen, Y Liu, F Ma, Z Liu, …
Citations: 55
Year: 2022
Material characterization to assess effectiveness of surface treatment to prevent joint deterioration from oxychloride formation mechanism
Authors: X Wang, S Sadati, P Taylor, C Li, X Wang, A Sha
Citations: 44
Year: 2019
Mechanistic-based comparisons of stabilised base and granular surface layers of low-volume roads
Authors: C Li, JC Ashlock, DJ White, PKR Vennapusa
Citations: 38
Year: 2019
Improvement of Asphalt-Aggregate Adhesion Using Plant Ash Byproduct
Authors: Z Liu, X Huang, A Sha, H Wang, J Chen, C Li
Citations: 36
Year: 2019
Morphology-based indices and recommended sampling sizes for using image-based methods to quantify degradations of compacted aggregate materials
Authors: C Li, J Zheng, Z Zhang, A Sha, J Li
Citations: 34
Year: 2020
In situ modulus reduction characteristics of stabilized pavement foundations by multichannel analysis of surface waves and falling weight deflectometer tests
Authors: C Li, JC Ashlock, S Lin, PKR Vennapusa
Citations: 34
Year: 2018
Mechanistic-based comparisons for freeze-thaw performance of stabilized unpaved roads
Authors: C Li, PKR Vennapusa, J Ashlock, DJ White
Citations: 32
Year: 2017
Influence of water on warm-modified asphalt: Views from adhesion, morphology and chemical characteristics
Conclusion
Zhang Licheng’s innovative research in energy-efficient driving behaviors and intelligent vehicle control, coupled with his strong academic background and real-world applications, positions him as a strong candidate for the Best Researcher Award. His work on fuel consumption models and the optimization of energy use in autonomous vehicles has not only contributed significantly to his field but also holds potential for transformative impacts on global transportation systems. Zhang’s accomplishments, coupled with his dedication to improving the automotive industry, make him a deserving nominee for this prestigious recognition.