Automobile Advance Alarm System Based on Monocular Vision Processing

Yi, Joo-young; Yang, Sanghoon; Jang, In-Gul; Chung, Jin-Gyun; Lim, Myoung-Seob

doi:10.1109/ivs.2007.4290152

Cited by 3 publications

(2 citation statements)

References 9 publications

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“…To verify the designed FlexRay system, the FlexRay system is applied to an automobile advance alarm system in vehicle applications [8]. The block diagram of the test environments is shown in Fig.…”

Section: Flexray Design Using Sdl Specification and Description mentioning

confidence: 99%

Implementation of FlexRay protocol with an automotive application

Jang

Kim

et al. 2008

2008 International SoC Design Conference

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FlexRay is a high-speed communications protocol with high flexibility and reliability. It was devised by automotive manufacturers and semiconductor vendors. FlexRay provides a high speed serial communication, time triggered bus and fault tolerant communication between electronic devices for automotive applications. In this paper, we first design the FlexRay communication controller, bus guardian protocol specification and function parts using SDL (Specification and Description Language). Then, the system is re-designed using Verilog HDL based on the SDL source. The FlexRay system is synthesized using Samsung 0.35 technology. It is shown that the designed system can operate in the frequency range up to 76 MHz. In addition, the FlexRay system is implemented using ALTERA Excalibur ARM EPXA4F672C3 with a bus driver chip AS8211. It is shown that the implemented system operates successfully in automobile advance alarm system in vehicle applications.

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Section: Flexray Design Using Sdl Specification and Description mentioning

confidence: 99%

Implementation of FlexRay protocol with an automotive application

Jang

Kim

et al. 2008

2008 International SoC Design Conference

View full text Add to dashboard Cite

show abstract

“…Therefore, visual navigation technology has become a hot issue in the intelligent vehicle research at present [1]- [3]. However, we usually face three main challenges: 1) real-time, it means the system must finish specific task in limited time; 2) accuracy, high recognition rate and low fault recognition rate; 3) robustness, the system should keep high recognition capability in different situations [4].…”

Section: Introductionmentioning

confidence: 99%

High Speed Lane Recognition under Complex Road Conditions

Gong

Wang

Zhai

et al. 2008

2008 IEEE Intelligent Vehicles Symposium

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To improve the speed and stability of lanes recognition under complex road conditions, a rapid detection algorithm combined with dynamic window and prior knowledge is proposed. The method of Grid is used to segment initial image and define the region of interest (ROI), then all the pixels are eliminated except those on the intersection of the grid lines, thus feature pixels of the lane edge in these intersections will be detected and can be used to generate some dynamic windows with the dilatation algorithm. Then, images are processed in these dynamic windows to obtain lane edge feature. Slope and intercept of the lane can be attained by Hough transformation. To obtain the correct lane information, the information obtained in current processing cycle will be judged and filtered by the prior knowledge. Experiments in structured road showed that the speed of image processing was about 22ms/frame and the proposed algorithm could meet the real-time and stability requirements of high-speed vehicle vision navigation system.

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Proposal of a driver assistance system based on video and radar data fusion

Gambi

Spinsante

2008

2008 16th International Conference on Software, Telecommunications and Computer Networks

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Automobile Advance Alarm System Based on Monocular Vision Processing

Cited by 3 publications

References 9 publications

Implementation of FlexRay protocol with an automotive application

Implementation of FlexRay protocol with an automotive application

High Speed Lane Recognition under Complex Road Conditions

Proposal of a driver assistance system based on video and radar data fusion

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