High-precision infrared pulse laser ranging for active vehicle anti-collision application

Chen, Yandong; Meng, Zhiqiang; Liu, Jinglin; Jiang, Heping

doi:10.1109/iceice.2011.5777775

Cited by 2 publications

(1 citation statement)

References 7 publications

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“…Hisaka et al [4] developed a on-board 'sensor' utilizing wireless communication devices for the collision avoidance, which used four wireless receivers of Zigbee are installed in the four corners of the driver's vehicle to detect vehicle and pedestrian at intersection. Chen et al [5] developed a high-precision infrared pulse laser ranging system based on FPGA and microcontroller Atmel16 for active vehicle anti-collision application. The system can accurately detect the distance between the cars, and can efficiently avoid traffic accident.…”

Section: Introductionmentioning

confidence: 99%

Research of Automobile Collision Avoidance System Based on Video Image Processing

Gao

Zhu

2015

AMM

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In this paper, an automobile collision avoidance system based on video image processing is proposed for vehicle active safety. Firstly, considering the requirement of real-time system, FPGA is responsible for the core task of video image processing. In the process, this paper introduces an image segmentation algorithm to extract the Region of Interest, a fast median filtering algorithm and an improved adaptive threshold Ostu segmentation algorithm. Secondly, in the design of alarm system, we use the STM32 chip which is based on Cortex-M3 kernel as the embedded platform. Finally, in order to analyze the data obtained by image processing and make smart decisions on the embedded platform, we establish a double parameter alarm mechanism of automobile security model. It can help the drivers to take appropriate hedging measures. The system in this paper has the characteristics of low cost, real-time and high reliability. Through the debugging and experiments, the system has reached the expected effect and met the requirements of automobile collision avoidance system.

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Section: Introductionmentioning

confidence: 99%