scholarly journals Driving Assistance System with Lane Change Detection

2021 ◽  
Vol 6 (3) ◽  
pp. 137-145
Author(s):  
Jia-Shing Sheu ◽  
Chun-Kang Tsai ◽  
Po-Tong Wang
Keyword(s):  
Color Space ◽  
Assistance System ◽  
Raspberry Pi ◽  
Color Space Conversion ◽  
Driving Assistance ◽  
Slope Change ◽  
Left And Right ◽  
Simple Technology ◽  
Embedded Image ◽  
Driving Assistance System

In this study, a simple technology for a self-driving system called “driver assistance system” is developed based on embedded image identification. The system consists of a camera, a Raspberry Pi board, and OpenCV. The camera is used to capture lane images, and the image noise is overcome through color space conversion, grayscale, Otsu thresholding, binarization, erosion, and dilation. Subsequently, two horizontal lines parallel to the X-axis with a fixed range and interval are used to detect left and right lane lines. The intersection points between the left and right lane lines and the two horizontal lines can be obtained, and can be used to calculate the slopes of the left and right lanes. Finally, the slope change of the left and right lanes and the offset of the lane intersection are determined to detect the deviation. When the angle of lanes changes drastically, the driver receives a deviation warning. The results of this study suggest that the proposed algorithm is 1.96 times faster than the conventional algorithm.

scholarly journals Smart driving assistance system using Raspberry Pi and actuator networks

2021 ◽  
Vol 1068 (1) ◽  
pp. 012022
Author(s):  
Saiful Anwar Che Ghani ◽  
Maurice Kettner ◽  
Ferhat Aslan ◽  
Fatimah Dzharuddin ◽  
Norazlianie Sazali
Keyword(s):  
Assistance System ◽  
Raspberry Pi ◽  
Driving Assistance ◽  
Driving Assistance System

Bus driving assistance system for town area by using ATmega328P microcontroller

2017 ◽  
Author(s):  
Mohamad Fauzi Zakaria ◽  
Tan Jiah Soon ◽  
Munzilah Md Rohani
Keyword(s):  
Assistance System ◽  
Driving Assistance ◽  
Driving Assistance System ◽  
Town Area

scholarly journals Built-in-self-test system for FPGA-based vehicle video-detection and distance measurement

2021 ◽  
Author(s):  
Md Forhad Ebn Anwar
Keyword(s):  
High Speed ◽  
Vision System ◽  
Test System ◽  
Distance Measurement ◽  
Assistance System ◽  
Project Work ◽  
Practical Calculation ◽  
Automatic Driving ◽  
Driving Assistance ◽  
Driving Assistance System

Collision of vehicles in highways are very frequent. Because of high speed (more than 100 km/hour), the momentum of collision is too high that leads sever casualty. Automatic Driving Assistance system can assist the vehicle operators to take decision based on realistic practical calculation on safety measures. It is always better to have third eye working parallel with human to avoid road accident. There are several technologies used to develop perfect driving assistance system to achieve higher accuracy in detection, identification and distance measurement of obstacles where vision based system is one of them. Mono-vision system provides cheap and fast solution rather stereo vision. This project work conducted with objective to comprehend computational complexity in implementation of mono-vison camera based object detection where system will generate warning if the detected object has a motion towards target. Processing and analyzing of captured video image is the focused mechanism of implementation and used internal image generator module to mimic actual video camera. Appeared size of the shape of object considered for the decision making. The simulated image pattern can change it’s dimension to represent vehicle movement in one direction (Back and forth). In this work the on-chip car image generation sub-system was proposed designed and partially implemented on the base of the FPGA where Xilinx Zynq-7010 (ZYNQ XC7Z010-1CLG400C) FPGA development board used. Keyword: Computer Vision, mono vision, image processing on FPGA, Automatic Driving Assistance, Vehicle Detection.

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