Virtual Reality Test Drive of Autonomous Vehicle
DENSO is one of the biggest tier one suppliers in the automotive industry, and one of its main goals is to provide solutions to the OEMs in the Automated Driving field. DENSO plans to increase its contribution to the development of automated driving technologies by enhancing the functionalities of existing techniques and invent new solutions.
The main objective of this project is to create a simulation of conditions in a specific, complicated US intersection and use the results to teach the autonomous driving system how to act in similar scenarios. The machine learning solutions that will be developed will help automated vehicles make proper driving decisions in a wide range different driving conditions.
More Information Coming Soon
Students who successfully match to this project team will be required to sign the following two documents in January 2018:
- Skill level All levels
- Students 5-7 Students
- Likely Majors A&D, CE, CS, DATA, ECE, EE, IOE, ISD-AUTO, ISD-GAME, MICDE, MIDAS, STATS
- Course Substitutions A&D Elec, CE MDE, Data Science, ECE Cognate, EE MDE, EECS 498, Honors, ISD-Auto, ISD-GAME, MICDE, MIDAS, ROB 590, SI, SI PEP, IOE Capstone
- IP & NDA Required? Yes
- Summer Opportunity See Complete Description for Details
Artificial Intelligence/Machine Learning (3-4 students)
Ideally already took, or are taking ME 599/ NA 599/ ROB 599/EECS 498: Self Driving Cars: Perception and Control in parallel
- EE, CE, CSE/CS-LSA, Robotics
Control Systems (1-2 students)
Planning to take ME461/EE460 or equivalent, familiar with MATLAB/SIMULINK
- EE, CE, CS, Robotics, ISD-AUTO, ISD-GAME
Applied Data Analysis & Statistics (2 students)
Numeric methods, statistics, stochastic calculus. R or other statistical packages, must also have basic coding experience
- MIDAS/MICDE, Data Science, STATS, IOE
Faculty Mentor: Huei Peng
Professor of Mechanical Engineering
Huei Peng received his Ph.D. in Mechanical Engineering from the University of California, Berkeley in 1992. He is now a Professor at the Department of Mechanical Engineering at the University of Michigan. His research interests include adaptive control and optimal control, with emphasis on their applications to vehicular and transportation systems. His current research focuses include design and control of electrified vehicles, and connected/automated vehicles.
In the last 10 years, he was involved in the design of several military and civilian concept vehicles, including FTTS, FMTV, Eaton/Fedex, and Super-HUMMWV—for both electric and hydraulic hybrid concepts. He served as the US Director of the DOE sponsored Clean Energy Research Center—Clean Vehicle Consortium, which supports more than 30 research projects related to the development of clean vehicles in US and China.
He currently serves as the Director of the University of Michigan Mcity, which studies connected and autonomous vehicle technologies and promotes their deployment. He has served as the PI or co-PI of more than 50 research projects, with a total funding of more than 45 million dollars. He has more than 250 technical publications, including 110 in referred journals and transactions and four books. His h-index is 63 according to the Google scholar analysis. The total number of citations to his work is more than 15,000. He believes in setting high expectation and helping students to exceed it by selecting forward-looking and high-impact research topics. One of his proudest achievements is that more than half of his Ph.D. students have each published at least one paper cited more than 100 times.
Huei Peng has been an active member of the Society of Automotive Engineers (SAE) and the American Society of Mechanical Engineers (ASME). He is both an SAE fellow and an ASME Fellow. He is a ChangJiang Scholar at the Tsinghua University of China.