Human-like Driving for Autonomous Vehicles using Vision-based Road Curvature Modeling

Li, Wei

doi:10.14257/ijhit.2013.6.5.10

Cited by 3 publications

(2 citation statements)

References 14 publications

(7 reference statements)

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“…However, this method is not as effective in detecting curved lanes as it is in detecting straight lanes. A few attempts have been made to solve this problem by dividing an image into multiple sections and applying the Hough transform to each section [12]. Accordingly, this study constructed a Hough transform algorithm to detect railway tracks.…”

Section: Algorithm To Detect and Recognize Railway Tracksmentioning

confidence: 99%

Enhancing Railway Maintenance Safety Using Open-Source Computer Vision

Shin¹,

Jin

Kim

2021

Journal of Advanced Transportation

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As high-speed railways continue to be constructed, more maintenance work is needed to ensure smooth operation. However, this leads to frequent accidents involving maintenance workers at the tracks. Although the number of such accidents is decreasing, there is an increase in the number of casualties. When a maintenance worker is hit by a train, it invariably results in a fatality; this is a serious social issue. To address this problem, this study utilized the tunnel monitoring system installed on trains to prevent railway accidents. This was achieved by using a system that uses image data from the tunnel monitoring system to recognize railway signs and railway tracks and detect maintenance workers on the tracks. Images of railway signs, tracks, and maintenance workers on the tracks were recorded through image data. The Computer Vision OpenCV library was utilized to extract the image data. A recognition and detection algorithm for railway signs, tracks, and maintenance workers was constructed to improve the accuracy of the developed prevention system.

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Section: Algorithm To Detect and Recognize Railway Tracksmentioning

confidence: 99%

Enhancing Railway Maintenance Safety Using Open-Source Computer Vision

Shin¹,

Jin

Kim

2021

Journal of Advanced Transportation

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“…One of the detecting methods is line detection which proposes the drivable area embraced by the road lines; to detect the lines thus defines the drivable area. On the other hand, line detection also provides a comparison basis for safety driving to develop a warning system to avoid collisions [3][4][5][6]. Moreover, as wireless communication is being widely applied nowadays, modern vehicles are usually equipped with the wireless communication components such as GPS, webcam, and WiFi modules.…”

Section: Introductionmentioning

confidence: 99%

Guidance control of vehicles based on visual feedback via internet

Lee

2015

J Wireless Com Network

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The proposed paper investigates the vehicle guidance control based on the visual information which is given by the webcam mounted on the vehicle. With the help of image processing techniques such as binarization, Canny edge detection method, and Hough transform, the road lines are thus identified, which means the drivable area can be defined. The proposed control scheme adopts a simple algorithm to guide the vehicle to run inside the drivable area within the road lines. The computation of defining drivable area and control algorithm is operated in a control center which connects the vehicle via WiFi wireless communication system. Similarly, the image information transmits back to the control center. Furthermore, the control center can not only monitor the vehicle inside some certain area but also control the vehicle dynamically in real time. To simplify the experimental setup, the drivable area is defined as the superhighway which allows only cars on the road. Two experimental results, one in a straight road and the other in a curved road, are given to demonstrate the effectiveness of the proposed guidance control system.

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A Survey on Driving Characteristics during Braking for Enhancement of Adaptive Cruise Control system

Lee¹,

Moon²,

Jeong³

et al. 2014

Advanced Science and Technology Letters

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Abstract. Adaptive cruise control (ACC) system Cruise Control is one of advanced driver assist systems (ADAS) for road vehicles. ACC systems have been designed and commercialized based on only ISO standards. ADAS needs more detailed design criteria. In this study, few parameters representing driving characteristics are drawn and the criteria for classification are suggested by securing and analyzing 77 driver vehicle interaction databases for highway driving. Drivers are classified by the suggested criteria and decelerating characteristics of each class are analyzed. Needs of discriminative standards considering an individual driver's driving characteristics for designing ACC algorithm are asserted in consideration of the analysis.

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Human-like Driving for Autonomous Vehicles using Vision-based Road Curvature Modeling

Abstract: Abstract

Cited by 3 publications

References 14 publications

Enhancing Railway Maintenance Safety Using Open-Source Computer Vision

Enhancing Railway Maintenance Safety Using Open-Source Computer Vision

Guidance control of vehicles based on visual feedback via internet

A Survey on Driving Characteristics during Braking for Enhancement of Adaptive Cruise Control system

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