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Subaru-24

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Subaru wants to implement advanced AI functionality in their Driver Monitoring System (DMS), leveraging passive IR (infrared) research. Students will develop advanced IR sensor applications for driver monitoring and consumer convenience that will be deployed in our prototype WRX, which is actively being displayed throughout the US at various auto shows, racetracks, and extraneous events.

Abstract:

As the automotive market for Advanced Driving Assistance Systems (ADAS) continues to grow, Subaru wants to implement more driver assistance systems to further improve safety in their cars. This aligns with our goal of reducing road fatalities in our cars to 0 by 2030. In addition, we seek to improve the customers user experience with these systems. Students will be expected to develop their skills in a range of topics, from computer vision and machine learning, to address functionality that incorporates one or more of the following: facial detection/recognition, gaze monitoring, alcohol detection, vehicle headlamp control, and several other features. Subaru wishes for the system to include passive IR sensors.

       

Impact:

The ability to improve driver safety, while also positively impacting their user experience, will provide Subaru with a more inclusive automotive design, leading to more effective and desirable systems. This will increase driver safety and comfort, customer satisfaction, and therefore Subaru’s position in the automotive market.

Scope:

Minimum Viable Product Deliverable (Minimum level of success)

  • Literature/background and internal knowledge review of technologies and internal Subaru knowledge in the relevant fields, including IR sensors, passive IR monitoring vs conventional active IR monitoring, artificial intelligence, facial recognition, driver monitoring, etc. 
  • Investigate a range of sensor use cases, and develop a prioritized roadmap of functionalities to incorporate into the student prototype sensor system 
  • Generation and evaluation of a range of solution concepts evaluated on ability to successfully achieve requirements, including risk, skills required, data required, cost, etc. 
  • Develop the first version of the functional prototype, and review with project stakeholders to ensure that it addresses at least two sensing challenges

Expected Final Deliverable (Expected level of success)

  • Incorporate stakeholder feedback into a second refined version of the tool
  • Verify the extent to which the prototype meets the requirements
  • Provide design information, verification data, and recommendations in a final report

Stretch Goal Opportunities: (High level of success)

  • Extend the accuracy and sophistication of use cases
  • Add additional situations and elements to the sensor capabilities
  • Optimize algorithm for effective use of computer (implement on a NVIDIA Jetson Orin Nano)
Below are the skills needed for this project. Students with the following relevant skills and interest, regardless of major, are encouraged to apply! This is a team based multidisciplinary project. Students on the team are not expected to have experience in all areas, but should be willing to learn and will be asked to perform a breadth of tasks throughout the two semester project.

Computer Vision and Machine Learning (3-4 Students)

Specific Skills: Computer vision for user recognition and machine learning to determine the driver’s head position, gaze, blood alcohol level, and/or other functionalities

Priority given to students who have completed EECS 442/445/492(or equivalent) and/or have relevant practical experience

Likely Majors: CS, ROB

Electronic Systems Development (2-3 Students)

Specific Skills: Sensor selection, integration, and optimization of computational resources

Prior or concurrent coursework and/or practical experience with applied electrical circuits and systems would be particularly helpful

Likely Majors: CE, EE, ROB

Additional Desired Skills/Knowledge/Experience

  • Strong judging skills to evaluate new technology and information
  • Effective communications across language barriers – particularly the ability to present results concisely
  • Ability to work effectively in a multi-disciplinary and multi-cultural team
  • Experience with cameras, lidar, or other sensors
  • Experience with computer vision and/or machine learning
  • Experience with control systems
  • Interest in cars and the automotive industry
  • Applicants who are interested in driving the test vehicle(s) must have a valid US driver’s license with no points. Subaru safety training will be provided and required to drive test vehicle(s). If you are chosen for the team, you will be asked to go through a driver’s license check

Sponsor Mentor

Kai Schiefer

Engineer – ADAS & Vehicle Performance Engineering

Kai has his BSc in Mechanical Engineering and MSc in Systems Engineering and Design from the University of Michigan. His primary focus area is ADAS.  He enjoys traveling around the world, and took a 3-month road trip across the US and into Mexico on his motorcycle, and he used to be on the UMich dance team, FunKtion.

Executive Mentor

John Hoo

Manager – ADAS & Vehicle Performance Engineering

John has been working for Subaru since 2017. He has his BSc in Materials Science & Engineering from Purdue University. His primary focus area is ADAS.  John received further training from Subaru in the USA and Japan, where he developed cross-language and cultural communication skills. To ensure the success of collaborative research efforts, he recently relocated to Michigan. In his spare time, he likes building PCs and motorcycling.

Faculty Mentor

P.C. Ku

Professor, Electrical Engineering

Professor Ku’s research focuses on energy-efficient optoelectronics using nanostructured materials; for example, how to reduce the laser threshold, how to increase the efficiency of light-emitting diodes and solar cells, how to efficiently transmit the data while maintaining the security, and how to reduce the power requirement for nonlinear optical devices.

Weekly Meetings: During the winter 2024 semester, the Subaru team will meet on North Campus on Wednesdays from 3:30 – 5:30 PM.

Work Location: Most of the work will take place on-campus in Ann Arbor. Periodically, project update meetings and work sessions may take place at the Subaru R&D facility in Van Buren Township. Use of Subaru test tracks for vehicle testing is highly welcomed (MDP will provide transportation to the R&D facility). 

Course Substitutions: CE MDE, ChE Elective, CS Capstone/MDE, EE MDE, CoE Honors, ROB 490, ROB 590, SI Elective/Cognate

Citizenship Requirements: This project is open to all students. Note: International students on an F-1 visa will be required to declare part time CPT during Winter 2024 and Fall 2024 terms.

IP/NDA: Students will sign IP/NDA document(s) that are unique to Subaru R&D.

Summer Project Activities: Students will be guaranteed an interview for a 2024 summer internship with Subaru Research & Development. The interviews will take place before the end of January 2024. Note: You must have the right work in the U.S.A indefinitely, without sponsorship, to participate in the summer internship program.

Learn more about the expectations for this type of MDP project

[email protected]
(734) 763-0818
117 Chrysler Center

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