M.Ing. (Electrical and Electronic Engineering) / Adaptive Cruise Control (ACC) is proposed to assist drivers tedious manual acceleration or braking of the vehicle, as well as with maintaining a safe headway time gap. This thesis proposes, simulates, and implements a vision-based ACC system which uses a single camera to obtain the clearance distance between the preceding vehicle and the ACC vehicle. A three-step vehicle detection framework is used to obtain the position of the lead vehicle in the image. The vehicle coordinates are used in conjunction with the lane width at that point to estimate the longitudinal clearance range. A Kalman filter filters this range signal and tracks the vehicle’s longitudinal position. Since image processing algorithms are computationally intensive, this document addresses how adaptive image cropping improves the update frequency of the vision-based range sensor. A basic model of a vehicle is then derived for which a Proportional-Integral (PI) controller with gain scheduling is used for ACC. A simulation of the system determines whether the ACC algorithm will work on an actual vehicle.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:uj/uj:13619 |
| Date | 25 June 2015 |
| Source Sets | South African National ETD Portal |
| Detected Language | English |
| Type | Thesis |
| Rights | University of Johannesburg |
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