A Fast and Robust Approach to Lane Marking Detection and Lane Tracking

Lipski, Christian; Scholz, B.; Berger, Kai; Linz, Christian; Stich, Timo; Magnor, Marcus

doi:10.1109/ssiai.2008.4512284

Cited by 61 publications

(26 citation statements)

References 9 publications

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“…Color-based Segmentation [37], [19], [38], [39], [40], [23], and [15] They perform in different colour spaces. [41] [41] is an improvement of MSER Segmentation [22] extended the case of one VP to multiple VPs, by applying a 2D-Hough transform.…”

Section: Segmentationmentioning

confidence: 99%

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Design of lane keeping assist system for autonomous vehicles

Mammeri

Boukerche

2015

2015 7th International Conference on New Technologies, Mobility and Security (NTMS)

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Lane detection and tracking and departure warning systems are important components of Intelligent Transportation Systems. They have particularly attracted great interest from industry and academia. Many architectures and commercial systems have been proposed in the literature. In this paper, we discuss the design of such systems regarding the following stages: pre-processing, detection, and tracking. For each stage, a short description of its working principle as well as their advantages and shortcomings are introduced. Our paper may possibly help in designing new systems that overcome and improve the shortcomings of current architectures.

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Section: Segmentationmentioning

confidence: 99%

“…Further, to make full use of the colour information of RGB images, some researchers deployed colour format conversion in their algorithm. For example, in [39], RGB images are converted to HSV. However, format conversion of coloured images may inevitably lose a certain amount of detail information in real scenarios.…”

Section: Segmentationmentioning

confidence: 99%

Design of lane keeping assist system for autonomous vehicles

Mammeri

Boukerche

2015

2015 7th International Conference on New Technologies, Mobility and Security (NTMS)

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“…The work proposed in [8], builds a Gaussian model for each pixel over the entire training set by accumulating only the hue and saturation from the HSI color space. The study proposed in [10] makes use of a multi-camera lane detection algorithm which operates in HSV color space. Another widely used algorithm for road segmentation is the watershed algorithm.…”

Section: Related Workmentioning

confidence: 99%

Knowlege on road information in sub-urban lane detection via multiple cue integration

Udawatta

Fernando

Pathirana

2010

2010 Eighth International Conference on ICT and Knowledge Engineering

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Detection of lane boundaries of a road based on the images or video taken by a video capturing device in a suburban environment is a challenging task. In this paper, a novel lane detection algorithm is proposed without considering camera parameters; which robustly detects lane boundaries in real-time especially for sub-urban roads. Initially, the proposed method fits the CIE L*a*b* transformed road chromaticity values (that is a* and b* values) to a bi-variate Gaussian model followed by the classification of road area based on Mahalanobis distance. Secondly, the classified road area acts as an arbitrary shaped region of interest (AROI) in order to extract blobs resulting from the filtered image by a two dimensional Gabor filter. This is considered as the first cue of images. Thirdly, another cue of images was employed in order to obtain an entropy image. Moreover, results from the color based image cue and entropy image cue were integrated following an outlier removing process. Finally, the correct road lane points are fitted with Bezier splines which act as control points that can form arbitrary shapes. The algorithm was implemented and experiments were carried out on sub-urban roads. The results show the effectiveness of the algorithm in producing more accurate lane boundaries on curvatures and other objects on the road.

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“…Certain techniques consider edges in grayscale images a feature for lane markings [10] while others might use steerable filters [11]. Recent advancements in image processing have led to methods utilizing color images to detect various lane features and to provide lane information [12].…”

Section: Iisimulation Approachmentioning

confidence: 99%

On board assistant to GPS navigation of vehicles

Reddy

Papachristou

Wolff

2009

Proceedings of the IEEE 2009 National Aerospace &Amp; Electronics Conference (NAECON)

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This study explores the use of inter vehicle communication to enhance road safety and traffic management. A vehicle's engine control unit (ECU) manages and controls various sensor signals and determines the output in terms of torque, fuel quantity and actuator positions. The data available in the ECU is however restricted only to that particular vehicle where it was generated. This work presents a scenario where critical data from each vehicle is broadcasted and a dynamic adhoc network of vehicles is formed. The algorithms in the ECU then detect possible collisions, decide which vehicle should take action and alert the driver with the most optimum response. The analysis presented here is based on simulation data.Traffic management is achieved with modules placed along the road, which collect the broadcasted data. Modules, after analyzing traffic density and average speeds, interact with neighboring modules. This traffic information is broadcasted to all vehicles in close proximity to the traffic modules. The vehicle uses this information along with details from the navigation system to reroute the automobile to avoid high traffic areas. I.INTRODUCTIONodern day automobiles consist of over 80 processors dealing with a plethora of information. Of these, the most important is the engine control unit (ECU), which deals with engine management, fuel management, dashboard information management, communication control and many other tasks. There is a lot of information present in the ECU especially in terms of vehicle speed, stability, acceleration, steering angle, brake position, average speed, trip meter etc. MHowever on road, the information present in one car is restricted only to that car and is not available for other users of the road. In our system, we hope that all cars are equipped with wireless cards so that there is possibility of interaction of one car with the outside world. In this system, all cars on the road will exchange information with each other. This will enable each car to detect collisions and alert the driver, thereby enhancing the safety and comfort of driving. The exchange would happen without the knowledge of driver and the driver would be prompted only when action is required.Currently existing systems use sensors to measure the proximity of the other vehicle for assisting the drivers. The main disadvantage of such an arrangement is that the sensors have a limited resolution. Also their accuracy reduces in case of low lighting or harsh environment conditions. For current cars, the benefit of this system would be limited to driver notification through dashboard warning lights and indicators of safety situations. The dashboard would alert the user of the imminent danger and can provide suitable solutions to avoid the same. A study of rear end and chain accidents [1] showed that 28% of accidents in US were caused by short car following distance. This number was close to half (13%) in Europe and was 33% in Presented at NAECON 2009. Australia. For preventing these rear end collisions, an increas...

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A Fast and Robust Approach to Lane Marking Detection and Lane Tracking

Abstract: We present a lane detection algorithm that robustly detects

Cited by 61 publications

References 9 publications

Design of lane keeping assist system for autonomous vehicles

Design of lane keeping assist system for autonomous vehicles

Knowlege on road information in sub-urban lane detection via multiple cue integration

On board assistant to GPS navigation of vehicles

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