projects
At Michigan Tech as a PI, my research has been supported by the following agencies.
Michigan Tech (2013-present):
11. USDOT FRA BAA IRS Project: co-PI, Leveraging Connected Highway Vehicle Platooning Technology to Improve the Efficiency and Effectiveness of Train Fleeting, 2019 - 2021.
10. USDOT FRA BAA IRS Project: PI, Developing Safe and Efficient Driving and Routing Strategies at Railroad Grade Crossing Based on Highway-Railway Connectivity, 2019 - 2022.
9. NSF CAREER Award: PI, CAREER: Tackling Congestion in Smart Cities via Data-Driven Optimization-Based Control of Connected and Automated Vehicles, 2019 - 2024.
Media coverage
8. MDOT Project: co-PI, Integration of Unmanned Aerial Systems Data Collection into Day-to-Day Usage for Transportation Infrastructure, 2019 - 2022. (PI: Colin Brooks, MTRI)
7. MEDC and MDOT Project: co-PI, Log Movement in the Superior Region – Rate and Capacity Based Analysis of Modal Shares, 2017 - 2019. (PI: Dr. Pasi Lautala, Civil and Environmental Engineering, MTU)
6. US DOE ARPA-E NEXTCAR Project: co-PI, Connected and Automated Control for Vehicle Dynamics and Powertrain Operation on a Light-Duty Multi-Mode Plug-in Hybrid Electric Vehicle, 2017 - 2021. (PI: Dr. Jeff Naber, Mechanical Engineering, MTU).
Some Media Coverages
DOE ARPA-e has put the MTU NEXTCAR project as the only one over 10 teams in their project spotlight - Traveling Smarter While Saving Energy, on June 22, 2017.
MTU news - Michigan Tech Automotive Energy Efficiency Research Receives Federal Award of $2.8 Million from US Department of Energy
HybridCARS - ARPA-E Funding $32Million for 10 Reduced-Energy Vehicles Projects.
DOE - DOE Announces 10 New Projects to Improve Connected and Automated Vehicle Efficiency.
Publications
Zhao, S., Zhang, K. A data-driven Model Predictive Control framework for robust Cooperative Adaptive Cruise Control using mobile sensing data. Accepted for presentation in the 97th Transportation Research Board Annual Meeting, January 7-11, 2018, in Washington, D.C.
5. MDOT UAV Project: co-PI, Implementation of Unmanned Aerial Vehicles (UAVs) for Assessment of Transportation Infrastructure - Phase II. (PI: Colin Brooks, MTRI), 2016 - 2018.
4. US DOT FTA’s Innovative Safety, Resiliency, and All-Hazards Emergency Response and Recovery Demonstration Program: PI, Coordinated Transit Response Planning and Operations Support Tools for Mitigating Impacts of All-Hazard Emergency Events. (Collaborate with Argonne National Laboratory), 2015 - 2017.
3. NSF-CMMI-CIS Program (1538105): PI, Collaborative Research: Improving Spatial Observability of Dynamic Traffic Systems through Active Mobile Sensor Networks and Crowdsourced Data. (Co-PI: Colin Brooks, MTRI, MTU; Collaborate with Arizona State University). 2015 - 2020.
Publications (*student co-author)
*Zhao, S., Zhang, K. A data-driven dynamic route choice model under uncertainty using connected vehicle trajectory data. Accepted for presentation in the 97th Transportation Research Board Annual Meeting, January 7-11, 2018, in Washington, D.C.
*Zhao, S., Zhang, K., Brooks, C., Banach, D., Aden, S. A comprehensive overview of improving traffic flow observability using UAVs as mobile sensors. Accepted for presentation in the 97th Transportation Research Board Annual Meeting, January 7-11, 2018, in Washington, D.C.
*Zhao, S., Zhang, K. Observing Individual Dynamic Choices of Activity Chains from Location-based Crowdsourced Data. Accepted by Transportation Research Part C. 2017.
*Zhao, S., Zhang, K. 2017. A Data-Driven Optimization Model to Observe Individual Dynamic Choices of Activity-Travel-Path using Connected Vehicles as Mobile Sensors. Accepted for presentation in the 96th Annual Meeting of Transportation Research Board, Washington D.C., 2017.
*Zhao, S., Zhang, K. 2017. Observing Space-Time Queueing Dynamics at a Signalized Intersection using Vehicles as Mobile Sensors. Accepted for presentation in the 96th Annual Meeting of Transportation Research Board, Washington D.C., 2017.
Education Activities
Dr. Zhang has served as a scientist client of the CS4760/CS5760: Human-Computer Interactions & Usability course in Spring 2017 to develop an app for mobile sensing from crowds to observe individual person activity-travel tracking system (iPATTS). A 6 CS undergraduate students will work as a team (Team iPatts) to design and implement the app idea, and 3 CS graduate students will work as consultants of this project. Dr. Zhang will meet with the team regularly throughout the development of the app. This app will be used in Dr. Zhang's Transportation Planning class in Fall 2017 for data collection. This app will be an example to integrating research and education from Dr. Zhang's on-going NSF CMMI-CIS- 1538105 project on mobile sensing and crowdsourced data.
2. MTU Research Excellence Fund: Co-PI, Evaluation of the impact of real-world traffic conditions on the battery performance and aging in electric vehicles. (PI: Lucia Gauchia, ECE, MTU)
Publications: (*student co-author)
*Jafari, M., Gauchia, A., Zhang, K., Gauchia, L., 2015. Simulation and Analysis of the Effect of Real-World Driving Styles in an EV Battery Performance and Aging. IEEE Transactions on Transportation Electrification. In press.
Gauchia, A., *Jafari, M., Zhang, K., Gauchia, L., 2015. REV-Cycle: A MATLAB-based Tool for Large-Data Analysis of Real-Life Driving Cycles for Electric Vehicles. 2015 IEEE International Transportation Electrification Conference and Expo (ITEC), Detroit, MI, June 14-17, 2015.
1. US DOT Project: PI, investigating the impact of high-speed passenger trains on freight train efficiency in shared railway corridors. (Collaborate with the University of Illinois at Urbana-Champaign)
Prior to joining Michigan Tech, I have worked on the following research projects at Argonne National Laboratory, Northwestern University, University of Maryland, Beijing Transportation Research Center, and Beijing Jiatong University.
Argonne National Laboratory (2010-2013):
US DOT Project: Leader of dynamic network modeling and traffic simulation for developing a planning and operations language for agent-based regional integrated simulation (POLARIS) .
Chicago OEMC Project: Leader for Task 2 : Evacuation Network Model and Developer of a software tool – EvacNet for developing an emergency evacuation model for the Chicago metropolitan area – Regional Transportation Simulation Tool for Evacuation Planning (RTSTEP).
Northwestern University (2007-2010):
SHRP 2 C04 Project: Improving Our Understanding of How Highway Congestion and Pricing Affect Travel Demand.
SHRP 2 L04 Project: Incorporating Reliability Performance Measures in Operations and Planning Modeling Tools.
US DOT Project: Implementation and Evaluation of Weather Responsive Traffic Estimation and Prediction System.
NCHRP 08-57 Project: Improved Framework and Tools for Highway Pricing Decisions.
University of Maryland (2004-2007):
US DOT Project: Programmed and improved utilities for an intelligent transportation network operational planning analysis software, DYNASMART-P.
US DOT Project: Created a dynamic micro-assignment modeling approach for integrated multimodal urban corridor management, DYNASMART-ICM, for the Baltimore-Washington Corridor CHART Network.
Texas DOT Project: Built a data interface for a real-time simulation-based traffic estimation and prediction system, DYNASMART-X.
European Commission Project: Led and implemented the Multimodal Freight Dynamic Network Simulation-Assignment Platform for the REORIENT corridor network in Europe.
Beijing Transportation Research Center (2003-2004):
Beijing Olympic Committee Project: Administrated and developed the Beijing Olympic Green Comprehensive Transportation Plan for Beijing 2008 Olympic Games (Collaborators: PTV AG, Germany, Parsons Brinckerhoff Inc., U.S.A., and GHD, Australia).
Beijing Science & Technology Commission Project: Coordinated and enhanced Beijing metropolitan transportation planning model (Collaborator: MVA, Hong Kong).
Beijing Jiaotong University (2000-2003):
University Funded Project: Developed a RTMS traffic data communication system.
Harbin Railway Administration Project: Designed a railway-based GIS data analysis system.
Chinese MOT Project: Conducted ITS data management for Beijing network.
Shandong Province Project: Generated transportation logistics plan for Shandong province.