Browsing by Subject "Feature selection and tracking"

Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    Development of an Innovative Prototype Lane Departure Warning System
    (Intelligent Transportation Systems Institute, Center for Transportation Studies, University of Minnesota, 2013-03) Yang, Jiann-Shiou
    Development of various techniques such as lane departure warning (LDW) systems can improve traffic safety significantly. An LDW system should be able to detect when the driver is in danger of departing the road and then trigger an alarm to warn the driver early enough to take corrective action. This report presents the development of a new prototype LDW system. It is mainly an image-based approach to find the vehicle's lateral characteristics and then uses that information to establish an operation algorithm to determine whether a warning signal should be issued based on the status of the vehicle deviating from its heading lane. The system developed takes a mixed approach by integrating the Lucas-Kanade (L-K) optical flow and the Hough transform-based lane detection methods in its implementation. The L-K point tracking is used when the lane boundaries cannot be detected, while the lane detection technique is used when they become available. Even though both techniques are used in the system, only one method is activated at any given time because each technique has its own advantages and also disadvantages. The developed LDW system was road tested on I-35, US-53, Rice Lake Road, Martin Road, and Jean Duluth Road. Overall, the system operates correctly as expected, with a false alarm occurring only roughly 1.18% of the operation time. This report presents the system implementation together with findings. Factors that could affect the system performance are also discussed.
  • Thumbnail Image
    Item
    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.