• Journal of Institute of Control, Robotics and Systems
• /
• v.21 no.2
• /
• pp.130-136
• /
• 2015

In this paper, we propose a robust curved lane marking detection method. Several lane detection methods have been proposed, however most of them have considered only straight lanes. Compared to the number of straight lane detection researches, less number of curved-lane detection researches has been investigated. This paper proposes a new curved lane detection and tracking method which is robust to various illumination conditions. First, the proposed methods detect straight lanes using a robust road feature image. Using the geometric relation between a vehicle camera and the road plane, several circle models are generated, which are later projected as curved lane models on the camera images. On the top of the detected straight lanes, the curved lane models are superimposed to match with the road feature image. Then, each curve model is voted based on the distribution of road features. Finally, the curve model with highest votes is selected as the true curve model. The performance and efficiency of the proposed algorithm are shown in experimental results.

• International Journal of Highway Engineering
• /
• v.16 no.1
• /
• pp.41-48
• /
• 2014

PURPOSES : The lane width of the domestic highway is 3.5 ~ 3.6m and it has been designed nationwide. However, the distribution of the average vehicle widths, rearview mirror widths and lateral wheel paths by region appear different. Then, lane spare widths may differ by region followingly. Thus, the flexible design of freeway lane widths is required. METHODS : The methodologies of this paper are as follows. First, vehicle widths rearview mirror widths lateral wheel paths of vehicles driven four national expressways were measured. Second, lane spare widths by vehicle widths were calculated. Third, lane spare widths reflecting rearview mirror widths were calculated by using interval estimation. Additionally, lane spare widths reflecting vehicles lateral wheel paths were calculated. RESULTS : The results of this paper are as follows. First, lane spare widths by vehicle widths ranges 0.83 to 0.95m. Second, lane spare widths reflecting rearview mirror widths ranges 0.518 to 0.747m at the confidence interval 95%. Third, lane spare widths reflecting vehicles' lateral wheel paths ranges -0.022 to 0.322m at the curved sections and the confidence interval 95%. CONCLUSIONS : It may be concluded that the present lane spare widths are relatively narrow at the curved section. Thus, there is a need to consider expanded lane widths at the curved sections. Additionally, there is a need to consider flexible design of lane widths by various conditions.

• Proceedings of the IEEK Conference
• /
• 2009.05a
• /
• pp.34-36
• /
• 2009

This paper proposes an effective lane detection algorithm using hugh transform and lane model. The proposed lane detection algorithm includes two major components, i.e., lane marks segmentation and an exact lane extraction using a novel postprocessing technique. The first step is to segment lane marks from background images using HSV color model. Then, a novel postprocessing is used to detect an exact lane using Hugh transform and lane models(linear and curved lane models). The postprocessing consists of three parts, i.e, thinning process, Hugh Transform and filtering process. We divide input image into three regions of interests(ROIs). Based on lane curve function(LCF), we can detect an exact lane from various extracted lane lines. The lane models(linear and curved lane mode]) are used in order to judge whether each lane segment is fit or not in each ROIs. Experimental results show that the proposed scheme is very effective in lane detection.

• 제어로봇시스템학회:학술대회논문집
• /
• 2002.10a
• /
• pp.107.2-107
• /
• 2002

The objective of this study is to propose a lane changing and keeping method on a curved road for an automatic guidance of a vehicle. It is well known that the speed control of a vehicle in a curved road is essential in terms of vehicle stability and passenger safety because centrifugal force makes a vehicle to be on out of lane. And it is also natural to avoid the collision with other cars or obstructions with keeping the stability and drivability. The vehicle pose and the road curvature were calculated by geometrically fusing sensor data from camera image, tachometer and steering wheel encoder though the Perception Net in which not only the state variables, but also the corresponding uncer...

• Journal of Institute of Control, Robotics and Systems
• /
• v.22 no.1
• /
• pp.1-7
• /
• 2016

ADAS (Advanced Driver Assistance Systems) requires not only real-time robust lane detection, both straight and curved, but also predicting upcoming steering direction by detecting the curvature of lanes. In this paper, a curvature lane detection algorithm is proposed to enhance the accuracy and detection rate based on using inverse perspective images and Gaussian Mixture Model (GMM) to segment the lanes from the background under various illumination condition. To increase the speed and accuracy of the lane detection, this paper used template matching, RANSAC and proposed post processing method. Through experiments, it is validated that the proposed algorithm can detect both straight and curved lanes as well as predicting the upcoming direction with 92.95% of detection accuracy and 50fps speed.

• International Journal of Highway Engineering
• /
• v.13 no.2
• /
• pp.57-65
• /
• 2011

In this study, estimated the minimum lane width for the curved section by analyzing of lateral sway distance and compared the lane width for result of this study and a precedent study for straight section on urban roads. Then suggested minimum lane width of road alignments and vehicle classes. The lane width of curved section that was investigated was 2.79m~3.40m. Analysis of frequency distribute and cumulative frequency distribution for lateral sway distance on the basis of 85% of the suggested vehicles. The result of study, minimum lane width for the curved section was 2.31m~2.58m in the case of small size car and 2.80m~3.27m in the case of large size car. Result of this study is judged that it is necessary to case for introduction of green transit, during road construction and construct a road for small size car. Expect result of this study can be used for the application of flexible design standard according the purpose of road designer.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.10 no.4
• /
• pp.304-310
• /
• 2017

In this paper, we propose the architecture of an IPM based lane detector for autonomous vehicles to detect and control the driving route along the curved lane. In the IPM image, we divide the area into two fields, Far/Near Field, and the lane candidate region is detected using the Hough transform to perform the matching for the curved lane. In autonomous vehicles, various algorithms must be embedded in the system. To reduce the system resources, we proposed a method to minimize the number of memory accesses to the image and various parameters on the external memory. The proposed circuit has 96% lane recognition rate and occupies 16% LUT, 5.9% FF and 29% BRAM in Xilinx XC7Z020. It processes Full-HD image at a rate of 42 fps at a 100 MHz operating clock.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.15 no.4
• /
• pp.81-90
• /
• 2016

As an autonomous driving vehicle (AV) need to cope with external road conditions by itself, its perception performance for road environment should be better than that of a human driver. A vision sensor, one of AV sensors, performs lane detection function to percept road environment for performing safe vehicle steering, which relates to define vehicle heading and lane departure prevention. Performance standards for a vision sensor in an ADAS(Advanced Driver Assistance System) focus on the function of 'driver assistance', not on the perception of 'independent situation'. So the performance requirements for a vision sensor in AV may different from those in an ADAS. In assuming that an AV keep previous steering due to lane detection failure, this study calculated lane departure distances between the AV location following curved road alignment and the other one driving to the straight in a curved section. We analysed lane departure distance and time with respect to the allowance of lane detection malfunction of an AV vision sensor. With the results, we found that an AV would encounter a critical lane departure situation if a vision sensor loses lane detection over 1 second. Therefore, it is concluded that the performance standards for an AV should contain more severe lane departure situations than those of an ADAS.

• International Journal of Automotive Technology
• /
• v.5 no.2
• /
• pp.69-76
• /
• 2004

This paper evaluates the effectiveness of four-wheel-steering system from the viewpoint of lane-keeping control theory. In this paper, the lane-keeping control system is designed on the basis of the four-wheel-steering automobiles whose desired steering response is realized with the application of model matching control. Two types of desired steering responses are presented in this paper. One is zero-sideslip response, the other one is steering response which realizes zero-phase-delay of lateral acceleration. Using simplified linear two degree-of-freedom bicycle model, simulation study and theoretical analysis are conducted to evaluate the lane-keeping control performance of active four-wheel-steering automobiles which have different desired steering responses. Finally, the evaluation is conducted on straight and curved roadway tracking maneuvers.

• Journal of the Semiconductor & Display Technology
• /
• v.15 no.1
• /
• pp.27-32
• /
• 2016

A new lane detection algorithm is proposed for the analysis of DNA fingerprints from a polymerase chain reaction (PCR) gel electrophoresis image. Although several research results have been previously reported, it is still challenging to extract lanes precisely from images having abrupt background brightness difference and bent lanes. We propose an edge based algorithm for calculating the average lane width and lane cycle. Our method adopts sub-pixel algorithm for extracting rising-edges and falling edges precisely and estimates the lane width and cycle by using k-means clustering algorithm. To handle the curved lanes, we partition the gel image into small portions, and track the lane centers in each partitioned image. 32 gel images including 534 lanes are used to evaluate the performance of our method. Experimental results show that our method is robust to images having background difference and bent lanes without any preprocessing.