Parking Assistance System

Abstract

Backing-out and heading-out manoeuvres in perpendicular or angle parking lots are one of the most dangerous manoeuvres, specially in cases where side parked cars block the driver view of gray scale camera was installed at the back-right side of a vehicle. A Finite State Machine (FSM) defined according to three CAN Bus the potential traffic flow. In this paper a new vision-based Advanced Driver Assistance System (ADAS) is proposed to automatically warn the driver in such scenarios. A monocular variables and a manual signal provided by the user is used to handle the activation/deactivation of the detection module.

The proposed oncoming traffic detection module uses Digital Image Processing as the field by MATLAB which computes spatiotemporal images from a set of pre-defined Scan -lines which are related to the position of the road. A novel spatio-temporal motion descriptor is proposed (STHOL) accounting for the number of lines, their orientation and length of the spatio-temporal images. Some parameters of the proposed descriptor are adapted for night time conditions. A Bayesian framework is then used to trigger the warning signal using multivariate normal density functions. Experiments are conducted on image data captured from a vehicle parked at different locations of an urban environment, including both daytime and night time lighting conditions. We demonstrate that the proposed approach provides robust results maintaining processing rates close to real time.