Dr. Licheng Zhang | Fuel Consumption | Best Researcher Award
Senior Engineer at Changβan University, China.
Dr. Zhang Licheng is a Senior Engineer at Changβan University, specializing in traffic engineering and control. He has a profound interest in sustainable driving behavior, fuel consumption modeling, and autonomous vehicle efficiency. With 33 publications and 10 patents to his name, his pioneering work in fuel consumption prediction models has advanced the understanding of vehicular dynamics. Dr. Zhangβs research integrates advanced technologies and data analytics to promote eco-driving and intelligent vehicle systems, making significant contributions to green transportation. He is a recognized thought leader in the domain, blending academic rigor with practical applications to impact the automotive industry globally.
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Education
Dr. Zhang Licheng completed his undergraduate studies in Computer Science and Technology, followed by a masterβs and doctoral degree in Traffic Engineering and Control. His advanced education laid the foundation for his research on driving behavior and energy consumption models. At Changβan University, his academic training focused on creating innovative methodologies to optimize driving efficiency and fuel usage. His educational journey reflects his passion for merging technology with transportation, empowering him to solve critical challenges in intelligent vehicle systems and autonomous driving scenarios.
Experience
Dr. Zhang brings over a decade of experience in automotive engineering and intelligent vehicle research. As a Senior Engineer at Changβan University, he has led numerous projects funded by prominent organizations, including the National Natural Science Foundation of China. His work emphasizes fuel-efficient driving strategies, autonomous vehicle simulations, and hybrid data modeling for energy optimization. Dr. Zhang has collaborated with global institutions, contributed to 33 journal publications, and mentored young researchers, shaping the future of green transportation technologies.
Research Interests
Dr. Zhangβs research explores energy-efficient driving behavior, integrating multi-source traffic data for ecological vehicle systems. He specializes in developing fuel consumption prediction models, autonomous driving strategies, and motion planning methods for lane-changing scenarios. His studies bridge the gap between driving behavior and environmental sustainability, contributing significantly to the design of energy-efficient autonomous vehicles. Dr. Zhangβs work also addresses real-world applications of digital twin testing and simulation for automated driving technologies.
Awards and Honors
Dr. Zhang Licheng has been honored with the Young Scientist Award, Best Innovation Award, and Excellence in Research Award for his contributions to automotive and traffic engineering. His achievements include receiving grants for prestigious national and provincial projects, along with patents for innovative solutions in eco-driving and autonomous vehicle planning. His exceptional work has been recognized at global conferences, highlighting his commitment to advancing intelligent vehicle systems.
Publications
Ma, S., Chen, C., Zhang, L., Zhang, J., Zhao, X.
Title: AMTrack: Transformer tracking via action information and mix-frequency features
Journal: Expert Systems with Applications
Year: 2025
Citations: 0
Zhang, L., Ya, J., Khattak, A.J., Peng, K., Guo, Y.
Title: Novel fuel consumption models integrating vehicular speed, acceleration, and jerk
Journal: Journal of Intelligent Transportation Systems: Technology, Planning, and Operations
Year: 2024
Citations: 0
Ma, S., Zhao, B., Zhang, L., Hou, Z., Zhao, X.
Title: Correlation Filter based on Trajectory Correction and Context Interference Suppression for Real-Time UAV Tracking
Journal: IEEE Transactions on Intelligent Vehicles
Year: 2024
Citations: 2
Zhang, L., Ya, J., Xu, Z., Xing, Y., Yang, R.
Title: Novel Neural-Network-Based Fuel Consumption Prediction Models Considering Vehicular Jerk
Journal: Electronics (Switzerland)
Year: 2023
Volume: 12
Issue: 17
Citations: 0
Wang, G., Zhang, L., Xu, Z., Qu, X.
Title: Predictability of Vehicle Fuel Consumption Using LSTM: Findings from Field Experiments
Journal: Journal of Transportation Engineering Part A: Systems
Year: 2023
Volume: 149
Issue: 5
Citations: 4
Peng, K., Xing, Y., Zhang, L., Song, Y., Ya, J.
Title: Quantitative Evaluation of Energy-saving Driving Based on Wavelet Transform
Conference: 7th IEEE International Conference on Transportation Information and Safety, ICTIS 2023
Year: 2023
Citations: 0
Zhang, L., Peng, K., Zhao, X., Khattak, A.J.
Title: New fuel consumption model considering vehicular speed, acceleration, and jerk
Journal: Journal of Intelligent Transportation Systems: Technology, Planning, and Operations
Year: 2023
Volume: 27
Citations: 12
Zhang, L., Zhang, T., Peng, K., Zhao, X., Xu, Z.
Title: Can Autonomous Vehicles Save Fuel? Findings from Field Experiments
Journal: Journal of Advanced Transportation
Year: 2022
Citations: 9
Wang, G., Zhang, L., Xu, Z., Wei, T., Qu, X.
Title: FuelNet: A precise fuel consumption prediction model using long short-term memory deep network for eco-driving
Conference: Energy Proceedings
Year: 2020
Citations: 0
Min, H., Zhao, X., Xu, Z., Zhang, L., Wang, R.
Title: Stereo Visual Odometry Based on Robust Features
Journal: Shanghai Jiaotong Daxue Xuebao/Journal of Shanghai Jiaotong University
Year: 2017
Citations: 2
Conclusion
Zhang Licheng is a strong candidate for the Best Researcher Award, owing to his innovative contributions to traffic engineering, eco-driving, and energy-efficient vehicular technologies. His well-rounded portfolio of research projects, patents, and publications underscores his dedication to advancing his field. While there is room for growth in global recognition and citation impact, Zhangβs accomplishments make him an exemplary researcher deserving of this prestigious award.