報告標題：Multi-scale modeling for investigating socio-technical interactions in transportation
ABSTRACT: New technologies and service modes are shaping the future of mobility. The interactions of human, society and technology can help improve people’s quality of life and mitigate environmental impacts from transportation. To fully exploit the interactions, we need holistic analysis techniques to integrate human/governance into cyber-physical scales modeling and component based design approaches. In this presentation, firstly I will present a system optimization framework to investigate optimal penetration strategies for a promising low-carbon fuel technology (i.e. cellulosic biofuel) in transportation fuel portfolio. In literature, the key knowledge gap is the technique to model uncertainty and dynamics of technology progress (learning by doing effect), market competition and policy interventions. Therefore, we employed multi-stage stochastic and dynamic optimization models to study time-dependent and adaptive decision-making processes to develop the advanced fuel technology. In addition, I adopted agent-based equilibrium model to understand competition of heterogeneous agents under policy guidance. We confirmed our strategies and results with real data from California’s implementation of Low Carbon Fuel Standard policy. The proposed framework, with small adjustments, can also guide studying new technology development in other sectors. Secondly, I will discuss a model that utilizes new-technology-enabled (connectivity, automation, etc.) integration of transportation and power grid system to improve system performance and people’s quality of life.
BIO –Dr. Yuche Chen will join the Department of Civil and Environmental Engineering at University of South Carolina (USC) as an Assistant Professor in January 2019. He earned his Ph.D. degree in Transportation Engineering from University of California Davis, in 2014 and his Master of Science in Management Science and Engineering from Zhejiang University in 2014. Before joining USC, Dr. Chen has worked for leading research institutes, including Oak Ridge National Laboratory, National Renewable Energy Laboratory, International Institute for Applied System Analysis, Texas A&M Transportation Institute, Vanderbilt University. Dr. Chen is broadly interested in decision making under uncertainty, empirical model prediction and validation with applications to cyber-physical systems. Dr. Chen serves as the Principle Investigators for projects funded by NSF, Department of Energy, Department of Transportation totaling at 1.4 million US dollar. He authored over 50 papers that are published in transportation journals (e.g., Transportation Research Part A, C, D), energy/environmental engineering journals (e.g., Applied Energy, Environmental Science and Technology, Energy Policy), and also featured in popular media outlets including Fox News, Scientific American, Daily Mail etc. His collaborative research with IIASA and ICCT led to the discovery of “Volkswagen Emission Scandal” in 2015. Dr. Chen was the recipient of Outstanding Achievement Award by Department of Energy in 2017, and Director’s Award by National Renewable Energy Laboratory in 2016. He is a committee member of Environmental Analysis in Transportation (ADC10) and Automated Transit System (AP020) in Transportation Research Board, National Academy of Sciences in United States.
(1) 數據驅動的城市交通控制與管理(Data-driven traffic operations and demand management)
(2) 智慧互聯城市中網絡實體系統建模與優化(Model prediction and optimization of cyber-physical systems in smart and connected communities)
(3)基于機器學習模型的生態駕駛輔助系統 (Machine learning based eco-driving assistant system)
(4) 交通環境污染與健康影響分析技術(Transportation air quality and health impacts of exposure)
The University of South Carolina is the state’s flagship university located in Columbia, South Carolina. It is currently ranked as one of the top 50 “Best Colleges” according to U.S. News and World Report (https://sc.edu/about/index.php). Dr. Chen’s research group will be part of the Center for Connected Multimodal Mobility (C2M2), a Tier 1 University Transportation Center granted by the US Department of Transportation. Its vision is to become a globally recognized multimodal mobility innovation center for moving people and goods, specializing in connectivity and data analytics.