Parallel parking is a difficult manoeuvre for drivers. The aim of this research was to develop a system to perform this manoeuvre autonomously, requiring no driver input at all.
The stages of this development were analysis of the kinematics of vehicles, the design of a simulator and prototype robot to demonstrate parking and the development of parking algorithms to achieve reverse- parallel parking at or above the standard of the learner drivers logbook.
Equations were derived to describe the motion of a vehicle. These were tested in a flexible Matlab simulation.
A remote control car was modified to be controlled via command line inputs or uploaded control law. A complete and successful set of laws has been documented and used to demonstrate the prototype robot in a parking scenario.
The final algorithms were able to successfully park the vehicle utilising only an ultrasonic sensor and encoders on the rear wheels. Calculations and parking are performed in real-time, taking substantially less time than a human driver would. This was only possible due to development of a highly optimised transform to analyse the sensor data.
Rogan graduated from the University of Adelaide in 2007 with
Honours in Mechatronics Engineering, and a Bachelor of
Mathematics & Computer Science. He is now undertaking a PhD.
Tim graduated from the University of Adelaide in 2006 with
Honours in Mechatronics Engineering. He is now employed at Sage
Automation.
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