Courses are together with exams the building blocks for modules. Please keep in mind that information on the contents, learning outcomes and, especially examination conditions are given on the module level only – see section "Assignment to Modules" above.
| additional remarks |
The lab course covers two important aspects of the control of automated vehicles, namely the generation of optimal paths and the design of tracking controllers which steer the vehicle along these paths. The students should implement the path planning problem as a constrained optimization problem and use several different numerical solvers to compute the optimal reference trajectories. The different optimization methods, as well as solvers, should be compared, and their strengths and weaknesses for the autonomous driving application should be detected.
For a given reference trajectory, different existing tracking control algorithms should be implemented, which keep the car close to the reference trajectory. The students should choose benchmark tests to evaluate the performance of different control algorithms. The implemented control algorithms should then be compared using the benchmark tests. |
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TUMonline entry
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