All Round Blind Spot Detection by Lens Condition Adaptation based on Rearview Camera Images

2013 ◽  
Author(s):  
Yasuhisa Hayakawa ◽  
Osamu Fukata
Keyword(s):  
Blind Spot ◽  
Spot Detection

scholarly journals Acceptance of Transportation Technologies by Aging Adults

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.

scholarly journals A Bluetooth-Low-Energy-Based Detection and Warning System for Vulnerable Road Users in the Blind Spot of Vehicles

Sensors ◽  
2020 ◽  
Vol 20 (9) ◽  
pp. 2727
Author(s):  
Nick De Raeve ◽  
Matthias de Schepper ◽  
Jo Verhaevert ◽  
Patrick Van Torre ◽  
Hendrik Rogier
Keyword(s):  
Real Life ◽  
Weighted Average ◽  
Warning System ◽  
Blind Spot ◽  
Low Energy ◽  
Bluetooth Low Energy ◽  
Road Users ◽  
Spot Detection ◽  
Raising Awareness ◽  
Vulnerable Road Users

Blind spot road accidents are a frequently occurring problem. Every year, several deaths are caused by this phenomenon, even though a lot of money is invested in raising awareness and in the development of prevention systems. In this paper, a blind spot detection and warning system is proposed, relying on Received Signal Strength Indicator (RSSI) measurements and Bluetooth Low Energy (BLE) wireless communication. The received RSSI samples are threshold-filtered, after which a weighted average is computed with a sliding window filter. The technique is validated by simulations and measurements. Finally, the strength of the proposed system is demonstrated with real-life measurements.

Vehicle Blind Spot Detection Using Anisotropic Magnetic Resistive Sensors

2005 ◽  
Author(s):  
Aric Shaffer ◽  
Gurpreet Aulakh ◽  
Anya Getman ◽  
Ronald Miller
Keyword(s):  
Blind Spot ◽  
Spot Detection

scholarly journals Wearable Bluetooth Low Energy Based Miniaturized Detection Node for Blind Spot Detection and Warning System on Vehicles

2021 ◽  
Author(s):  
Nick De Raeve ◽  
Quinten van den Brande ◽  
Matthias De Schepper ◽  
Jo Verhaevert ◽  
Patrick Van Torre ◽  
...  
Keyword(s):  
Warning System ◽  
Blind Spot ◽  
Low Energy ◽  
Bluetooth Low Energy ◽  
Spot Detection

scholarly journals Camera-Based Blind Spot Detection with a General Purpose Lightweight Neural Network

Electronics ◽  
2019 ◽  
Vol 8 (2) ◽  
pp. 233 ◽  
Author(s):  
Yiming Zhao ◽  
Lin Bai ◽  
Yecheng Lyu ◽  
Xinming Huang
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Embedded System ◽  
High Speed ◽  
Blind Spot ◽  
General Purpose ◽  
Driver Assistance Systems ◽  
Spot Detection ◽  
Novel Method ◽  
Series Of Experiments

Blind spot detection is an important feature of Advanced Driver Assistance Systems (ADAS). In this paper, we provide a camera-based deep learning method that accurately detects other vehicles in the blind spot, replacing the traditional higher cost solution using radars. The recent breakthrough of deep learning algorithms shows extraordinary performance when applied to many computer vision tasks. Many new convolutional neural network (CNN) structures have been proposed and most of the networks are very deep in order to achieve the state-of-art performance when evaluated with benchmarks. However, blind spot detection, as a real-time embedded system application, requires high speed processing and low computational complexity. Hereby, we propose a novel method that transfers blind spot detection to an image classification task. Subsequently, a series of experiments are conducted to design an efficient neural network by comparing some of the latest deep learning models. Furthermore, we create a dataset with more than 10,000 labeled images using the blind spot view camera mounted on a test vehicle. Finally, we train the proposed deep learning model and evaluate its performance on the dataset.

Millimeter Wave Radar for Automotive Blind Spot Detection System

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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