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Smart and Autonomous Vehicle (Certificate)

Description

The Graduate Certificate in Smart and Autonomous Vehicles (SAV) provides students and practicing engineers the technical skills and systems knowledge needed to be effective contributors to the development of self-driving vehicles and Advanced Driver-Assistance Systems (ADAS). The certificate exposes students to the broad component areas of motion capability, sensing and perception (with a focus on computer vision), mapping and localization, and algorithms for control and cognition.

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    Program Learning Outcomes

    Students completing the SAV certificate program will have the ability to:

    1. Explain the basic levels of driving automation and operation of common ADAS technologies, as well as the operation of common intelligent transportation system architectures.
    2. Explain the principles of operation of the various sensors and actuators common to autonomous and semi-autonomous vehicles.
    3. Analyze the motion of a ground vehicle based on its mechanical architecture.
    4. Interpret sensory input data through perception algorithms, including image processing algorithms (for such tasks as lane and obstacle recognition).
    5. Map an unknown environment.
    6. Estimate aspects of a vehicle’s motion (position, velocity, etc.) based on sensor data.
    7. Design algorithms for the real-time control of an autonomous vehicle and its subsystems.
    8. Apply and develop high-level cognitive algorithms for perception, and the navigation and planning of an autonomous vehicle.
    9. Implement vehicle, subsystem, and communication algorithms in software and/or hardware.
    10. Employ simulation tools to implement and validate algorithms pertaining to vehicle and subsystem operation.
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    Admission Requirements

    Applicants will be considered if they have excellent academic records, having earned a minimum GPA of 3.0 in obtaining an undergraduate degree in engineering, or a closely related field with sufficient background. All incoming students will require experience with algorithmic thinking and programming in an established language (MATLAB, C++, Java, Python, etc.). Applicants will also need a strong core in mathematics including calculus, differential equations, matrix algebra, and probability. Students should further have experience with the analysis and design of feedback systems, including in the frequency domain.
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    Certificate Requirements (15 credits)

    This is a 15-17 credit (five courses, plus labs if necessary) certificate program. Nine credits (three courses) are required core courses, and 6-8 credits (two courses, plus labs if necessary) are electives which may be chosen from the list below.  Students must maintain a 3.0 grade point average at the graduate level in order for the certificate to be granted. A student whose cumulative quality point average is below 3.0 is automatically placed on academic probation.

    Required Courses (9 credit hours)

    • ELEE 5200 Autonomous Mobility Robotics (3 credits)
    • ELEE 5700 Controls II (3 credits)
    • ELEE 5920 Image Processing and Computer (3 credits)

    Elective courses (choose 2 courses, plus labs if necessary, 6-8 credit hours)

    • ELEE 5000 Hardware Software Integration (3 credits)
    • ELEE 5400 Computational Intelligence (3 credits)
    • ELEE 5620 Random Variables and Random Processes (3 credits)
    • ELEE 5685 Wireless Sensor Networks (3 credits)
    • ELEE 5695 Wireless Sensor Networks Laboratory (1 credit)
    • ELEE 5770 Embedded Systems (3 credits)
    • ELEE 5790 Embedded Systems Laboratory (1 credits)
    • ELEE 5940 Probabilistic Robotics (3 credits)
    • ENGR 5220 Sensors and Actuators (3 credits)
    • MENG 5760 Vehicle Dynamics (3 credits)
    • CSSE 5480 Artificial Intelligence (3 credits)

     

Program Contact Information

Dr. David Pistrui
Director of Graduate Recruiting
Engineering Graduate Professional Programs
Telephone: 313-993-3378
Email: pistruda@udmercy.edu

Dr. Darrell Kleinke
Director: Engineering Graduate Programs
Telephone: 313-993-1140
Email: kleinked@udmercy.edu

Valarie Steppes-Glisson, Administrator
Advanced Electric Vehicle Program Office - Engineering 270
Telephone: 313-993-1128
Fax: 313-993-1955
Email: glissovs@udmercy.edu
 

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