Browsing by Subject "Heading angle"

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    Estimation of vehicle lateral position using the optical flow method
    (2013-05) Shrestha, Rini
    With the increasing number of vehicles on the road the number of accidents have also been increasing. Development of various techniques such as lane departure warning systems that helps drivers to assist in driving can help reduce the number of accidents significantly. In this thesis, we attempt to develop such lane departure warning system by estimating the vehicle's lateral position. The lateral position of vehicle can be known if the heading angle of the vehicle can be determined. Therefore, this study focuses on determining heading angle and works toward development of the lane departure warning system based on image processing techniques. An in-vehicle camera is used to capture the images of the road in real time. The system then uses homography on this front - view images of the road to remove the perspective effect and transform the images such that the obtained resulting images represent as if they were observed from the top. The histogram equalization is also applied to the images to increase the global contrast by spreading out the most frequent intensity values. Shi and Tomasi corner detection technique has been used to find significant features (corners) in the images and Lucas - Kanade optical flow to track those corners in following images. The heading angle, and thus the lateral displacement, is determined by relating these tracked corners. As part of the study, a number of road tests were conducted on different roads of Duluth, MN and the findings based on the road tests are discussed.
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    Estimation of Vehicle's Lateral Position via the Lucas-Kanade Optical Flow Method
    (Intelligent Transportation Systems Institute, Center for Transportation Studies, University of Minnesota, 2012-09) Yang, Jiann-Shiou
    The use of rumble strips on roads has proven to be an effective means of providing drivers lane departure warning (LDW). However, rumble strips require an infrastructure and do not exist on a majority of roadways. Furthermore, rumble strips present a difficult issue of where to establish the rumble-strip distance threshold. To develop an effective virtual rumble-strip LDW system where the rumble-strip threshold is allowed to vary according to the risk of the vehicle departing the road, it is essential to know the vehicle’s lateral characteristics; in particular, the vehicle’s lateral position and speed. In this report, we use image processing via an in-vehicle camera to estimate the vehicle’s lateral position and speed. The lateral position is estimated by determining the vehicle’s heading angle via a homography and the Lucas-Kanade optical flow techniques; while the lateral speed is determined via the heading angle and the vehicle’s On Board Diagnostic (OBD)-II forward speed data access. The detail of our approach is presented in this report together with our findings. Our approach will only need the minimal set of information to characterize the vehicle lateral characteristics, and therefore, makes it more feasible in a vehicle application.