Lane departure warning system LDWS has been regarded as an efficient method to lessen the damages of road traffic accident resulting from driver fatigue or inattention. Lane detection is one of the key techniques for LDWS. To overcome the contradiction between complexity of algorithm and the real-time requirement for vehicle onboard system, this paper introduces a new lane detection method base...

Effect of driver’s awareness (e.g., to estimate the speed and arrival time of another vehicle) on the lane changing maneuver is discussed. “Scope awareness” is defined as the visibility which is required for the driver to make a visual perception about road condition and the speed of vehicle that appears in the target lane for lane changing in the road. Cellular automaton based simulation model...

In this paper, we propose an integrated system that combines vehicle detection, lane detection, and vehicle distance estimation in a collaborative manner. Adaptive search windows for vehicles provide constraints on the width between lanes. By exploiting the constraints, the search space for lane detection can be efficiently reduced. We employ local patch constraints for lane detection to improv...

This thesis presents a tool for efficient query and analysis of MPEG encoded video. The image sequences for the video are obtained via a vehicle-mounted forward-looking camera. The tool accepts queries that signify both temporal and geometric events as the vehicle traverses common roadways, such as " identify portions of the video where the vehicle is making a lane change maneuver, " or " ident...

Evaluating the effectiveness and benefits of driver assistance systems is crucial for improving the system performance. In this paper, we propose a novel framework for testing and evaluating lane departure correction systems at a low cost by using lane departure events reproduced from naturalistic driving data. First, 529,096 lane departure events were extracted from the Safety Pilot Model Depl...

In this paper we propose a robust lane detection and tracking method by combining particle filters with the particle swarm optimization method. This method mainly uses the particle filters to detect and track the local optimum of the lane model in the input image and then seeks the global optimal solution of the lane model by a particle swarm optimization method. The particle filter can effecti...

Live-wire type techniques for interactive image segmentation are of practical use for various applications such as medical image analysis, digital image composition, etc. Intelligent scissors [5] and live wire [8] are the representative techniques of this type, which are based on a graph search over an entire image. Another technique called live lane [8] is also based on a graph search but loca...

Lane detection is one of the most important tasks in self-driving. Due to various complex scenarios (e.g., severe occlusion, ambiguous lanes, etc.) and sparse supervisory signals inherent lane annotations, task still challenging. Thus, it difficult for ordinary convolutional neural network (CNN) train general scenes catch subtle feature from raw image. In this paper, we present a novel module n...

This paper presents a novel algorithm for nighttime detection of the lane markers painted on a road at night. First of all, the proposed algorithm uses neighborhood average filtering, 8-directional Sobel operator and thresholding segmentation based on OTSU’s to handle raw lane images taken from a digital CCD camera. Secondly, combining intensity map and gradient map, we analyze the distribution...

Many global challenges, including obesity, health care costs, and climate change, could be addressed in part by increasing the use of bicycles for transportation. Concern about the safety of bicycling on roadways is frequently cited as a deterrent to increasing bicycle use in the USA. The use of effective signage along roadways might help alleviate these concerns by increasing knowledge about t...