A Study on the Development of the Driver's Intensive Warning System during Tunnel Driving Based on Real-Time Vehicle Detection and Distance Estimation

2021 ◽  
Author(s):  
JongBae Kim
Keyword(s):  
Real Time ◽  
Distance Estimation ◽  
Warning System ◽  
Vehicle Detection

Real-Time Vehicle Detection using a Single Rear Camera for a Blind Spot Warning System

2012 ◽  
Vol 5 (1) ◽  
pp. 146-153 ◽  
Author(s):  
Chikao Tsuchiya ◽  
Shinya Tanaka ◽  
Hiroyuki Furusho ◽  
Kenji Nishida ◽  
Takio Kurita
Keyword(s):  
Real Time ◽  
Warning System ◽  
Vehicle Detection ◽  
Blind Spot

scholarly journals Real Time Vehicle Detection, Tracking, and Inter-vehicle Distance Estimation based on Stereovision and Deep Learning using YOLOv3

2021 ◽  
Vol 12 (8) ◽  
Author(s):  
Omar BOURJA ◽  
Hatim DERROUZ ◽  
Hamd AIT ABDELALI ◽  
Abdelilah MAACH ◽  
Rachid OULAD HAJ THAMI ◽  
...  
Keyword(s):  
Deep Learning ◽  
Real Time ◽  
Distance Estimation ◽  
Vehicle Detection

scholarly journals Efficient Vehicle Detection and Distance Estimation Based on Aggregated Channel Features and Inverse Perspective Mapping from a Single Camera

Symmetry ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 1205
Author(s):  
Jong Bae Kim
Keyword(s):  
Real Time ◽  
Autonomous Vehicles ◽  
Distance Estimation ◽  
Vehicle Detection ◽  
Input Image ◽  
Three Dimensions ◽  
Real Time Processing ◽  
Time Processing ◽  
Histograms Of Oriented Gradients ◽  
Inverse Perspective Mapping

In this paper a method for detecting and estimating the distance of a vehicle driving in front using a single black-box camera installed in a vehicle was proposed. In order to apply the proposed method to autonomous vehicles, it was required to reduce the throughput and speed-up the processing. To do this, the proposed method decomposed the input image into multiple-resolution images for real-time processing and then extracted the aggregated channel features (ACFs). The idea was to extract only the most important features from images at different resolutions symmetrically. A method of detecting an object and a method of estimating a vehicle’s distance from a bird’s eye view through inverse perspective mapping (IPM) were applied. In the proposed method, ACFs were used to generate the AdaBoost-based vehicle detector. The ACFs were extracted from the LUV color, edge gradient, and orientation (histograms of oriented gradients) of the input image. Subsequently, by applying IPM and transforming a 2D input image into 3D by generating an image projected in three dimensions, the distance between the detected vehicle and the autonomous vehicle was detected. The proposed method was applied in a real-world road environment and showed accurate results for vehicle detection and distance estimation in real-time processing. Thus, it was showed that our method is applicable to autonomous vehicles.

Towards A Vision-Based Forward Collision Warning System

2020 ◽  
Author(s):  
S. M. Saleh ◽  
H. M. Saleh ◽  
N. T. Toure ◽  
Wolfram Hardt
Keyword(s):  
Real Time ◽  
Distance Estimation ◽  
Warning System ◽  
Region Of Interest ◽  
Depth Map ◽  
Threshold Value ◽  
Driving Safety ◽  
Annual Number ◽  
Robust Solution ◽  
On The Road

The annual number of road deaths is still increasing, especially in less developed and developing countries. Road accidents are the 5th cause of death and the leading reason for death among young people between 5 and 29 years of age in 2030. In this study, a robust solution is implemented by integrating object recognition with distance estimation to maximize driving safety. The proposed system will be able to detect common objects within the region of interest on the road and estimate how far these objects are from the camera position. The system will trigger an alarm to attract the driver’s attention in real time when the distance to one of the detected objects is less than a predefined threshold value. In this work YOLO (You Only Look Once) approach is used to detect the objects in real time and the properties of the depth map based on deep learning is applied to estimate the distance at a given point

Safety Monitoring and Warning System for Subway Construction Workers using Wearable Technology

2019 ◽  
Vol 13 ◽  
Author(s):  
Jun-hua Chen ◽  
Da-hu Wang ◽  
Cun-yuan Sun
Keyword(s):  
Real Time ◽  
Video Surveillance ◽  
Early Warning ◽  
Warning System ◽  
Safety Monitoring ◽  
Wearable Technology ◽  
Construction Workers ◽  
Great Success ◽  
Subway Construction ◽  
Monitoring And Early Warning

Objective: This study focused on the application of wearable technology in the safety monitoring and early warning for subway construction workers. Methods: With the help of real-time video surveillance and RFID positioning which was applied in the construction has realized the real-time monitoring and early warning of on-site construction to a certain extent, but there are still some problems. Real-time video surveillance technology relies on monitoring equipment, while the location of the equipment is fixed, so it is difficult to meet the full coverage of the construction site. However, wearable technologies can solve this problem, they have outstanding performance in collecting workers’ information, especially physiological state data and positioning data. Meanwhile, wearable technology has no impact on work and is not subject to the inference of dynamic environment. Results and conclusion: The first time the system applied to subway construction was a great success. During the construction of the station, the number of occurrences of safety warnings was 43 times, but the number of occurrences of safety accidents was 0, which showed that the safety monitoring and early warning system played a significant role and worked out perfectly.

A Novel System for Nighttime Vehicle Detection Based on Foveal Classifiers With Real-Time Performance

2021 ◽  
pp. 1-13
Author(s):  
Andres Bell ◽  
Tomas Mantecon ◽  
Cesar Diaz ◽  
Carlos R. del-Blanco ◽  
Fernando Jaureguizar ◽  
...  
Keyword(s):  
Real Time ◽  
Vehicle Detection ◽  
Time Performance

scholarly journals An Augmented Warning System for Pedestrians: User Interface Design and Algorithm Development

2021 ◽  
Vol 11 (16) ◽  
pp. 7197
Author(s):  
Yourui Tong ◽  
Bochen Jia ◽  
Shan Bao
Keyword(s):  
User Interface ◽  
Real Time ◽  
Interface Design ◽  
Situational Awareness ◽  
Warning System ◽  
User Interface Design ◽  
Warning Systems ◽  
Projection Algorithms ◽  
Time Projection ◽  
Timely Warning

Warning pedestrians of oncoming vehicles is critical to improving pedestrian safety. Due to the limitations of a pedestrian’s carrying capacity, it is crucial to find an effective solution to provide warnings to pedestrians in real-time. Limited numbers of studies focused on warning pedestrians of oncoming vehicles. Few studies focused on developing visual warning systems for pedestrians through wearable devices. In this study, various real-time projection algorithms were developed to provide accurate warning information in a timely way. A pilot study was completed to test the algorithm and the user interface design. The projection algorithms can update the warning information and correctly fit it into an easy-to-understand interface. By using this system, timely warning information can be sent to those pedestrians who have lower situational awareness or obstructed view to protect them from potential collisions. It can work well when the sightline is blocked by obstructions.

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