Development of Smart Vehicle Blind Spot Detection System Based on 24 GHz Radar Sensors

Road safety has become more concern due to the number of accidents that keeps increasing every year. The safety system includes from simple installation such as seat belt, air bag and rear camera to more complicated and intelligent system such as braking assist, lane change assist and blind spot monitoring. This paper proposed a Smart Vehicle Blind Spot Detection System (VBDS) to observe the blind spot region based on ISO 17387: 2008(E). This system is mounted with two programmable 24 GHz radar sensors on the left and right rear side of the car. In addition, this system provides an audible and visual alert to the driver if the system senses any vehicles in the blind spot region using buzzer and LED, respectively. To analyze the performance of the system, test had been conducted at different demography condition. The accuracy of the system is analyzed by comparing number of vehicles detected within blind spot region and ground truth data. This system will alert the driver automatically to ensure the driver safety and reduce road accident. As conclusion, the system had been proofed applicable to use at different demography condition.

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Acceptance of Transportation Technologies by Aging Adults

Innovation in Aging ◽

10.1093/geroni/igaa057.1822 ◽

2020 ◽

Vol 4 (Supplement_1) ◽

pp. 555-555

Author(s):

Neil Charness ◽

Dustin Souders ◽

Ryan Best ◽

Nelson Roque ◽

JongSung Yoon ◽

...

Keyword(s):

Older Adults ◽

Older Adult ◽

Detection System ◽

Blind Spot ◽

Driving Performance ◽

Older Drivers ◽

Crash Risk ◽

Warning Systems ◽

Risk Of Death ◽

Spot Detection

Abstract Older adults are at greater risk of death and serious injury in transportation crashes which have been increasing in older adult cohorts relative to younger cohorts. Can technology provide a safer road environment? Even if technology can mitigate crash risk, is it acceptable to older road users? We outline the results from several studies that tested 1) whether advanced driver assistance systems (ADAS) can improve older adult driving performance, 2) older adults’ acceptance of ADAS and Autonomous Vehicle (AV) systems, and 3) perceptions of value for ADAS systems, particularly for blind-spot detection systems. We found that collision avoidance warning systems improved older adult simulator driving performance, but not lane departure warning systems. In a young to middle-aged sample the factor “concern with AV” showed age effects with older drivers less favorable. Older drivers, however, valued an active blind spot detection system more than younger drivers.

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Millimeter Wave Radar for Automotive Blind Spot Detection System

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.694-697.1008 ◽

2013 ◽

Vol 694-697 ◽

pp. 1008-1012

Author(s):

Shou Xiao Li ◽

Yun Xia Cao ◽

Xin Bi

Keyword(s):

Millimeter Wave ◽

Detection System ◽

Blind Spot ◽

Radar Sensor ◽

Simulation Data ◽

Millimeter Wave Radar ◽

Target Signal ◽

Spot Detection ◽

Wave Radar ◽

Rearview Mirror

Considering the problem of rearview mirror blind spot during driving, the paper studied and designed the blind spot detection system based on MMW radar. Radar was installed at an appropriate position on the detection target signal by transmitting, when another car enter the detecting area, the small alarm light beside A pillar would shine or alarm few times, to remind drivers careful change road. And the effect would not effect by weather or time. For the radar sensor application environment, triangle wave LFMCW can effectively solve the speed from the coupling phenomenon. The paper showed experimental and simulation data.

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Robust vehicle detection and tracking method for Blind Spot Detection System by using vision sensors

2014 Second World Conference on Complex Systems (WCCS) ◽

10.1109/icocs.2014.7060984 ◽

2014 ◽

Cited By ~ 2

Author(s):

Seunghwan Baek ◽

Heungseob Kim ◽

Kwangsuck Boo

Keyword(s):

Detection System ◽

Vehicle Detection ◽

Blind Spot ◽

Tracking Method ◽

Detection And Tracking ◽

Spot Detection ◽

Vehicle Detection And Tracking ◽

Vision Sensors

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A Study on Development of the Camera-Based Blind Spot Detection System Using the Deep Learning Methodology

Applied Sciences ◽

10.3390/app9142941 ◽

2019 ◽

Vol 9 (14) ◽

pp. 2941 ◽

Cited By ~ 1

Author(s):

Donghwoon Kwon ◽

Ritesh Malaiya ◽

Geumchae Yoon ◽

Jeong-Tak Ryu ◽

Su-Young Pi

Keyword(s):

Autonomous Vehicles ◽

Detection System ◽

Autonomous Vehicle ◽

Blind Spot ◽

Detection Accuracy ◽

Source Codes ◽

Spot Detection ◽

Research Goal ◽

Safety Features ◽

Fully Connected

One of the recent news headlines is that a pedestrian was killed by an autonomous vehicle because safety features in this vehicle did not detect an object on a road correctly. Due to this accident, some global automobile companies announced plans to postpone development of an autonomous vehicle. Furthermore, there is no doubt about the importance of safety features for autonomous vehicles. For this reason, our research goal is the development of a very safe and lightweight camera-based blind spot detection system, which can be applied to future autonomous vehicles. The blind spot detection system was implemented in open source software. Approximately 2000 vehicle images and 9000 non-vehicle images were adopted for training the Fully Connected Network (FCN) model. Other data processing concepts such as the Histogram of Oriented Gradients (HOG), heat map, and thresholding were also employed. We achieved 99.43% training accuracy and 98.99% testing accuracy of the FCN model, respectively. Source codes with respect to all the methodologies were then deployed to an off-the-shelf embedded board for actual testing on a road. Actual testing was conducted with consideration of various factors, and we confirmed 93.75% average detection accuracy with three false positives.

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