Advanced Driver Assistance Systems (ADAS), such as Adaptive Cruise Control, Lane Keeping Assist, and Lane Changing Assist, can be tested on the Automated Driving Lab. For this purpose, references are generated that are tracked by using appropriate controllers for longitudinal and lateral vehicle dynamics.
Moreover, cooperation between vehicles via "Vehicle-to-Vehicle" or "Vehicle-to-Infrastructure" communication can increase the efficiency of many automated driving maneuvers.
The focus at the Institute of Automation and Control lies hence on the reference generation and tracking in automated and cooperative driving.
Setup, implementation and control design for a model truck driving backwards (Master thesis)
State estimation for improved position detection of model trucks (Bachelor thesis)
Comparison of different steering angle controllers (Bachelor thesis)
Setup of a model vehicle using BeagleBone Boards (Bachelor thesis)
Reference Generation by 5th-order Polynomials on BeagleBone Board (Bachelor thesis)
Parking assist for a model vehicle
Prediction of other road users on motorways (Bachelor thesis)
Model predicitve motion planning for automated highway driving (Master thesis)
Position tracking using AprilTags with four WebCams
Construction of 2 model vehicles
Projection of the environment (street) by beamer
Different open projects are available for projects (Bachelor/Master) and theses (Bachelor/Master).
Environments used for the Testbed:
Simulation: MATLAB / Simulink, optionally coupled with "SUMO" (Simulation of Urban Mobility), see http://sumo.dlr.de/wiki/ Experiments: MATLAB / Simulink with BeagleBone Support and MATLAB RealTime Toolbox
Useful skills: MATLAB/Simulink, control theory basics
Further information can be found here. For questions please contact Jasmina Zubača or Tobias Renzler
Wir verwenden Cookies, um Ihnen in Zukunft weiterhin das bestmögliche Service zur Verfügung stellen zu können. Nähere Informationen sowie Widerrufsmöglichkeiten finden Sie in der Datenschutzerklärung. Präferenzen speichern