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 is (1) creating driveable simulations of real roads (e.g., North Campus, I-94 from Ann  Arbor to the Detroit airport, (2) creating GUIs that allow us to rapidly simulate specific scenarios  (e.g., lane changes at specific times or places), (3) developing software to simulate partially and fully automated vehicles using the Wizard of Oz method, and (4) interfacing a low-cost motion base for the driver to provide increased realism. The team is also producing documentation, both written and video summaries, so the applications developed can be used by students and research staff without strong computer backgrounds. In addition to software development, students will learn team skills, how to build prototypes, and eventually conduct experiments with users of software/hardware to validate ease of use and functional requirements.

Meeting time and location:

To accommodate team members in other time zones who can only participate virtually, our MDP team meets Mondays at 9:00 pm – 10:00 pm ET using Zoom as well as in-person. In addition, subteams meet by themselves about once per week at a time of their choosing, with each subteam deciding if they want to meet in person, virtually, or some combination, which we have done since March 2020. Some work can be done on students’ own computers, but most are not fast enough and students spend too many weeks trying to get the CARLA software to work. For that reason, we have set up 3 computers with CARLA and steering wheel/pedal assemblies and a motion base in the UMTRI Building, room 310 on North Campus, 2901 Baxter Road. For safety reasons, that software is not to be operated remotely.

Remote positions available: Some roles are available for remote participation; motion-base is in-person. 

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 PILeaders are typically those that have some degree of experience with the team and those roles are not determined by academic level. Often, the leaders are undergraduate students.  Students do not sign up for teams. Rather, when they apply, they have skills that could be useful to one or more subteams. Once everyone is onboard, the entire team looks at what needs to be done, and then matches the project needs, what students are interested in, and the skills they have to organize the project. This could include serving on multiple subteams to help with coordination.

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 (7 Students)

Specific Skills: Virtual world creation, programming of GUI, data management

Preferred Skills: Coding (In Python and C), data management skills, experience with creating gaming platforms, knowledge of CARLA, Roadrunner, and Unreal engine

Likely Majors: SE/CSLSA, Information, Data Science, EECS 280 is most important, EECS 281 is valuable

Motion Platform Algorithm Engineer (3 Students)

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

Preferred Skills: Experience with robots, knowledge of Python, knowledge of CARLA, Roadrunner

Likely Majors: Mechanical Engineering, Robotics

Human Factors, Virtual Road Systems, and Interface Subteam (2 Students)

Specific Skills: Develop scenarios and interface between driver/occupants, simulator and road systems, support GUI development

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

Apprentice Researchers (3 Students)

Requirements: Interest in project material, willingness to develop skills. Students will be integrated into the operations of a subteam. 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 62nd 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: CEE, CSE/CS-LSA, CE, EE, SI, IOE, ME, ROBO, SE, URP, Any

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

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

IP/NDA: Students who successfully match to this project team will be required to sign an Intellectual Property (IP) Agreement prior to participation in January 2023

Location: All roles are available for remote participation.

Course Substitutions: Honors

How to Apply

Full MDP project list & application information can be found here