scholarly journals Lane Detection and Lane Departure Warning System

2021 ◽  
Vol 10 (3) ◽  
pp. 2212-2218
Keyword(s):  
Autonomous Vehicles ◽  
Warning System ◽  
Region Of Interest ◽  
Detection Algorithm ◽  
Lane Detection ◽  
Road Accidents ◽  
Lane Departure ◽  
Clustering And Classification ◽  
Canny Edge ◽  
Boundary Information

Lane detection is important for autonomous vehicles. For this reason, many approaches use lane boundary information to locate the vehicle inside the street, or to integrate GPS-based localization. Advanced driverassistance systems are developed to assist drivers in the driving process reducing road accidents. In this work, we present an end-to-end system for lane identification, clustering and classification, based on two cascaded neural networks, that runs in real-time. The first step is camera calibration which is used to remove the effect of lens distortion. Then a canny edge detection algorithm finds the edges of the images. Then the region of interest (ROI) is selected. The ROI is actually based on the rectangular shape appearing at the bottom of the image. ROI removes the unwanted region in the image. The potential lane markers are then determined using the Hough transform to analyze lane boundaries. Once the lane pixels are found, these pixels are continuously scanned to obtain the best linear regression analysis.It is qualified to be applied on highways and urban roadways. It also has been successfully verified in sunny, and rainy conditions for both day and night.

scholarly journals Robust Lane Detection and Tracking Algorithm for Steering Assist Systems

Machines ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 10
Author(s):  
Mihail-Alexandru Andrei ◽  
Costin-Anton Boiangiu ◽  
Nicolae Tarbă ◽  
Mihai-Lucian Voncilă
Keyword(s):  
Warning System ◽  
Region Of Interest ◽  
Original Method ◽  
Lane Detection ◽  
Light Sources ◽  
Detection And Tracking ◽  
Lane Departure ◽  
Increase In Accuracy ◽  
Safety Systems ◽  
Distinct Features

Modern vehicles rely on a multitude of sensors and cameras to both understand the environment around them and assist the driver in different situations. Lane detection is an overall process as it can be used in safety systems such as the lane departure warning system (LDWS). Lane detection may be used in steering assist systems, especially useful at night in the absence of light sources. Although developing such a system can be done simply by using global positioning system (GPS) maps, it is dependent on an internet connection or GPS signal, elements that may be absent in some locations. Because of this, such systems should also rely on computer vision algorithms. In this paper, we improve upon an existing lane detection method, by changing two distinct features, which in turn leads to better optimization and false lane marker rejection. We propose using a probabilistic Hough transform, instead of a regular one, as well as using a parallelogram region of interest (ROI), instead of a trapezoidal one. By using these two methods we obtain an increase in overall runtime of approximately 30%, as well as an increase in accuracy of up to 3%, compared to the original method.

scholarly journals Robust lane detection algorithm based on triangular lane model

Filomat ◽  
2018 ◽  
Vol 32 (5) ◽  
pp. 1639-1647
Author(s):  
Young Park ◽  
Sung Na ◽  
Qun Wei ◽  
Ki Seong ◽  
Jyung Lee ◽  
...  
Keyword(s):  
Extraction Method ◽  
Industrial Revolution ◽  
Near Field ◽  
Warning System ◽  
Detection Algorithm ◽  
Lane Detection ◽  
Feature Points ◽  
Lane Departure ◽  
Cloudy Weather ◽  
Forward Collision Warning

Recently, various technologies and sciences are developed for fourth industrial revolution which includes artificial intelligence, robotics, internet of things, 3-D printing, and autonomous transportation. The autonomous transportation is one of the fourth industrial technology, and has been studying for safety driving. Accurate lane detection and lane departure warning system is very important for autonomous transportation. However, conventional methods have some problems of applying real-driving such as extracting miss lanes under cloudy weather and vehicle disturbance situations. In order to solve the real driving problems, we propose a new lane detection technique for lane departure and forward collision warning system using a single in-vehicle camera. The proposed method consists of triangular lane model, feature points extraction method. In the near field, a triangular lane model is used to approximate a pair of lane boundaries. Subsequently, feature points extraction method based on hyperbola curve model is applied to obtain lane curvature in the far field. Mathematical B-spline applied to feature points for curved lane fitting. Simulation results show that the proposed lane detection and tracking method has good performance.

scholarly journals A Real-Time Lane Detection Algorithm Based on Intelligent CCD Parameters Regulation

2012 ◽  
Vol 2012 ◽  
pp. 1-16 ◽  
Author(s):  
Ping-shu Ge ◽  
Lie Guo ◽  
Guo-kai Xu ◽  
Rong-hui Zhang ◽  
Tao Zhang
Keyword(s):  
Real Time ◽  
Road Traffic ◽  
Warning System ◽  
Detection Algorithm ◽  
Lane Detection ◽  
The Real ◽  
Lane Departure ◽  
Lane Line ◽  
Onboard System ◽  
Complexity Of Algorithm

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 based on intelligent CCD parameters regulation. In order to improve the real-time capability of the system, a CCD parameters regulating method is proposed which enhances the contrast between lane line and road surfaces and reduces image noise, so it lays a good foundation for the following lane detection. Hough transform algorithm is improved by selection and classification of seed points. Finally the lane line is extracted through some restrictions. Experimental results verify the effectiveness of the proposed method, which improves not only real-time capability but also the accuracy of the system.

scholarly journals Robust and real-time multi-lane and single lane detection in Indian highway scenarios

2021 ◽  
Vol 309 ◽  
pp. 01016
Author(s):  
A. Sai Hanuman ◽  
G. Prasanna Kumar
Keyword(s):  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Region Of Interest ◽  
Weather Conditions ◽  
Vital Role ◽  
Lane Detection ◽  
Fundamental Aspect ◽  
Detection Approach ◽  
Lane Line ◽  
Canny Edge

In the Advanced Driver Assistance System (ADAS), lane detection plays a vital role to avoid road accidents of an Autonomous vehicle. Also, autonomous vehicles should be able to navigate by themselves, in-order to do, it needs to understand its surrounding conditions like a human. So that vehicle can determine its path in streets and highways it can maintain lane manoeuvre. Also, It has become the most fundamental aspect to consider in current ADAS research. One of the major hurdles in self-driving vehicle research is identifying the curved lanes, multiple lanes with challenging light, and weather conditions, especially in Indian highway scenarios. As it is a vision-based lane detection approach we are using OpenCV library which consists of multiple algorithms like the optimization of canny edge detection to find out the edges, features of the lane and Hough Transform for lane line generation and apply on the particular region of interest.

A Novel Method for Tramcar Anti-Collision Warning System Based on Monocular Vision

2012 ◽  
Vol 430-432 ◽  
pp. 1871-1876
Author(s):  
Hui Bo Bi ◽  
Xiao Dong Xian ◽  
Li Juan Huang
Keyword(s):  
Software Design ◽  
Early Warning System ◽  
Warning System ◽  
Detection Algorithm ◽  
Lane Detection ◽  
Monocular Vision ◽  
System Construction ◽  
Collision Warning ◽  
Lane Width ◽  
Novel Method

For the problem of tramcar collision accident in coal mine underground, a monocular vision-based tramcar anti-collision warning system based on ARM and FPGA was designed and implemented. In this paper, we present an improved fast lane detection algorithm based on Hough transform. Besides, a new distance measurement and early-warning system based on the invariance of the lane width is proposed. System construction, hardware architecture and software design are given in detail. The experiment results show that the precision and speed of the system can satisfy the application requirement.

A Novel Real-Time Lighting-Invariant Lane Departure Warning System

2018 ◽  
pp. 231-252
Author(s):  
Yassin Kortli ◽  
Mehrez Marzougui ◽  
Mohamed Atri
Keyword(s):  
Real Time ◽  
Traffic Accidents ◽  
Essential Element ◽  
Warning System ◽  
Lane Detection ◽  
Accuracy Evaluation ◽  
Lane Departure Warning ◽  
Lighting Conditions ◽  
Lane Departure ◽  
Driving Assistance

In recent years, in order to minimize traffic accidents, developing driving assistance systems for security has attracted much attention. Lane detection is an essential element of avoiding accidents and enhancing driving security. In this chapter, the authors implement a novel real-time lighting-invariant lane departure warning system. The proposed methodology works well in different lighting conditions, such as in poor conditions. The experimental results and accuracy evaluation indicates the efficiency of the system proposed for lane detection. The correct detection rate averages 97% and exceeds 95.6% in poor conditions. Furthermore, the entire process has only 29 ms per frame.

Algorithm of Lane Detection on an Appropriate Limited Region

2013 ◽  
Vol 433-435 ◽  
pp. 267-272
Author(s):  
Xing Ma ◽  
Chun Yang Mu ◽  
Chun Tao Zhang ◽  
Lu Ming Zhang
Keyword(s):  
Urban Environment ◽  
Hough Transform ◽  
Region Of Interest ◽  
Detection Algorithm ◽  
Lane Detection ◽  
Limited Region ◽  
Feature Based

This paper proposed a lane detection algorithm for urban environment. The algorithm was concerned on selecting an appropriate limited region of interest (ROI) by OTSU segmentation. Then candidates of lane markers were extracted by Canny, finally the lane boundaries were detected by Hough transform. The limited ROI helps to identification lane in an appropriate region. This process have the effect of enhancement in the speed of operation. The proposed algorithm was simulated in MATLAB. The test databases were shared by Fondazione Bruno Kessler (FBK). The experiments show that lane boundaries can be detected correctly although they are fade. Feature-based method is usually affected by intension of image. Several characteristics of roads need to be considered further for detection more precisely.

Lane Detection Based on Improved Canny Detector and Least Square Fitting

2013 ◽  
Vol 765-767 ◽  
pp. 2383-2387 ◽  
Author(s):  
Guang Hua Chen ◽  
Wen Zhou ◽  
Feng Jiao Wang ◽  
Bin Jie Xiao ◽  
Sun Fang Dai
Keyword(s):  
Least Square Method ◽  
Detection Algorithm ◽  
Lane Detection ◽  
Least Square ◽  
Edge Detector ◽  
Canny Edge Detector ◽  
Least Square Fitting ◽  
Video Images ◽  
Canny Edge ◽  
Single Pixel

The video images of road monitoring system contain noise, which blurs the difference between the lane and the background. The lane detection algorithm based on traditional Canny edge detector hardly detects the single-pixel lane accurately and it produces pseudo lane. The paper proposes an effective lane detection method based on improved Canny edge detector and least square fitting. The proposed method improves the dual-threshold selection of traditional Canny detector by using the histogram concavity analysis, which sets the optimal threshold automatically. The least square method is used to fit the feature points of detected edges to accurate and single-pixel wide lane. Experimental results show that the proposed method detects the lane of video images accurately in the noise environment.

Real-time illumination invariant lane detection for lane departure warning system

2015 ◽  
Vol 42 (4) ◽  
pp. 1816-1824 ◽  
Author(s):  
Jongin Son ◽  
Hunjae Yoo ◽  
Sanghoon Kim ◽  
Kwanghoon Sohn
Keyword(s):  
Real Time ◽  
Warning System ◽  
Lane Detection ◽  
Lane Departure Warning ◽  
Illumination Invariant ◽  
Lane Departure

scholarly journals Lane Detection for Autonomous Vehicles using Open CV Library

2020 ◽  
Vol 6 (12) ◽  
pp. 176-180
Author(s):  
Aarushi Mittal and Narinder Kaur
Keyword(s):  
Hough Transform ◽  
Autonomous Vehicles ◽  
Region Of Interest ◽  
Traffic Signals ◽  
Lane Detection ◽  
Polar Coordinates ◽  
Cartesian Coordinates ◽  
Path Discovery

For vehicles to have the option to drive without anyone else, they have to comprehend their encompassing world like human drivers, so they can explore their way in roads, pause at stop signs and traffic signals, and try not to hit impediments, for example, different vehicles and pedestrians. In view of the issues experienced in identifying objects via self-governing vehicles an exertion has been made to show path discovery utilizing OpenCV library. The explanation and method for picking grayscale rather than shading, distinguishing and detecting edges in an image, selecting region of interest, applying Hough Transform and choosing polar coordinates over Cartesian coordinates has been discussed.

Sign in / Sign up

Export Citation Format

Share Document