A robust and efficient lane detection system is an essential component of Lane Departure Warning Systems, which are commonly used in many vision-based Driver Assistance Systems (DAS) in intelligent transportation. Various computation platforms have been proposed in the past few years for the implementation of driver assistance systems (e.g., PC, laptop, integrated chips, PlayStation, and so on)...

This manuscript develops a visual lane detection algorithm using the Hough transform to detect strong lines in a road image as candidates for lane boundaries. The search space in the Hough transform is reduced by searching for lane boundaries where they were detected in the previous video frame. The perspective transform is applied to determine the position and orientation of candidate lines, w...

We brieey review diierent models used nowadays in car following and lane changing for road traac simulation. We compare four recent simulators of traac and we focus on the approaches used in these simulators for performing car following and lane changing. Then we present in more details the algorithms used in the Hipertrans simulator for executing these car following and lane changing tasks.

This paper presents a data fusion algorithm which is able to robustly estimate the Time-to-Lane-Crossing (TLC) of a vehicle traveling along a lane on the basis of road images, collected by an on-board videocamera, and kinematic data coming from car sensors. This algorithm is instrumental to built Lane Departure Warning Systems (LDWS) with enhanced predictive capabilities which allow the generat...

Lane-border detection is one of the best developed modules in vision-based driver assistance systems today. However, still there is a need to improve for challenging road and traffic situations, and also a need to design tools for quantitative performance evaluation. This paper discusses and refines a method to generate ground truth for lane markings from recorded video, applies two lane-detect...

This paper presents a way to e ciently use lane detection techniques known from driver assistance systems to assist in obstacle detection for autonomous trains. On the one hand, there are several properties that can be exploited to improve conventional lane detection algorithms when used for railway applications. The heavily changing visual appearance of the tracks is compensated by very e ecti...

Road lane detection and tracking methods are the state of the art in present driver assistance systems. However, lane detection methods that exploit the parallel processing capabilities of heterogeneous high performance computing devices such as FPGAs (or GPUs), a technology that potentially will replace ECUs in a coming generation of cars, are a rare subject of interest. In this thesis a road ...

As important components of intelligent transportation system, lane detection and tracking (LDT) and lane departure warning (LDW) systems have attracted great interest from the computer vision community over the past few years. Conversely, lane markings recognition (LMR) systems received surprisingly little attention. This thesis proposed a real-time lane assisting framework for intelligent vehi...