Motor vehicles must be safe and easy to use. Assessments are performed both in real vehicles and in driving simulators. However, many driving simulators are too expensive to purchase, too complex to use, take too long to program, and sometimes lack the desired functional characteristics. The goal of this project is to build an easytouse driving simulator platform through the creative use of free software (e.g., OpenDS, Roadrunner), simple hardware, and student creativity to develop a driving simulator suitable to support research on driver distraction, driver workload, and driver interfaces for partiallyautomated vehicles.

Our team will build virtual roadways and scenarios suitable for simple experiments; we will create virtual worlds that can be explored in the simulator, starting locally. In addition, by improving an integrated hardwaresoftware system, students will learn software to support virtual reality, build prototypes, and conduct experiments with users of software/hardware to validate ease of use and functional requirements. The team will communicate how the simulator works via technical documentation as well as innovative video and audio summaries.

Meeting time and location:

For academic credit, our MDP course is classified as a hybrid course but will mainly meet remotely, following university public health informed guidelines. Our MDP team meets Mondays at 9:00pm10:00 pm ET due to team members in other time zones) using video conferencing. Our lab is located at the UMTRI Building, 2901 Baxter Road; Online meeting options are available as needed; team has been successfully working remotely since March 2020Each subteam arranges a convenient time to meet and work together following university guidelines. twoterm commitment will begin January 2021.

Team organization:

This team has flexible subteams that allow students to deepen their learning. The teams are flexibly structured to enhance creativity and opportunity for student growth. Each of the subteams has a student team leader that reports to the faculty PIs.

More information

Firstyear undergraduates through masters graduate students are welcome to apply, and all will be encouraged to stay on the team for more than the twosemester minimum. Leadership roles are available in the lab, and experienced students will be a natural fit for these positions as their knowledge grows over time.

Software Engineer (3 Students)

Specific Skills: Virtual world creation, programming, coding, data management

Preferred Skills: Coding and data management skills, experience with creating gaming platforms, Blender, OpenDS, Roadrunner, and ArcGISCityEngine skills

Likely Majors: SE/CSLSA, Information, Data Science

Motion Platform Algorithm Engineer (3 Students)

Specific Skills: : Develop motion platform algorithms and interface with software

Preferred Skills: Experience with simulation in OpenDSRoadrunner, Unreal Engine

Likely Majors: Mechanical Engineering, Robotics

Human Factors, Virtual Road Systems, and Interface Subteam (3 Students)

Specific Skills: Develop scenarios and interface between driver/occupants, simulator and road systems, development with open source such as OpenStreetMap

Likely Majors: Civil Engineering, Urban Planning/Transportation Planning, Systems Engineering, IOE

Apprentice Researchers (3 Students)

Requirements: Interest in project material, willingness to develop skills. Open to first-year and second-year undergraduate students ONLY.

Likely Majors: Any

Faculty Sponsor

Paul Green, Ph.D.

Dr. Green is a research professor in UMTRI’s Driver Interface Group and an adjunct research professor in the University of Michigan Department of Industrial and Operations Engineering (IOE). He teaches automotive human factors and human-computer interaction classes. He is the leader of U-M’s Human Factors Engineering Short Course, the flagship continuing-education course in the profession, now approaching its 60th year. Dr. Green also leads a research team that focuses on driver distraction, driver workload, workload managers, navigation-system design, and motor-vehicle controls and displays. More recently, the team has expanded their focus to include partially automated vehicles. That research makes extensive use of instrumented cars and driving simulators.

Students: 12-16

Likely Majors: Civil Eng, CSE/CSLSA, CE, EE, Information Science, IOE, ME, Robotics, Systems Engineering, Urban Planning/Transportation Planning, Any

Summer Opportunity: Summer research fellowships may be available for qualifying students

Citizenship Requirements: This project is open to all students on campus.

IP: Students who successfully match to this project team will be required to sign an Intellectual Property (IP) Agreement prior to participation in January 2021.

Course Substitutions: Honors