scholarly journals A NOVEL APPROACH TO CAMERA CALIBRATION METHOD FOR SMART PHONES UNDER ROAD ENVIRONMENT

2016 ◽  
Vol XLI-B5 ◽  
pp. 49-54
Author(s):  
Bijun Lee ◽  
Jian Zhou ◽  
Maosheng Ye ◽  
Yuan Guo
Keyword(s):  
Camera Calibration ◽  
Smart Phone ◽  
Warning System ◽  
Image Data ◽  
Calibration Method ◽  
Smart Phones ◽  
Driver Assistance Systems ◽  
The Road ◽  
Novel Approach ◽  
On The Road

Monocular vision-based lane departure warning system has been increasingly used in advanced driver assistance systems (ADAS). By the use of the lane mark detection and identification, we proposed an automatic and efficient camera calibration method for smart phones. At first, we can detect the lane marker feature in a perspective space and calculate edges of lane markers in image sequences. Second, because of the width of lane marker and road lane is fixed under the standard structural road environment, we can automatically build a transformation matrix between perspective space and 3D space and get a local map in vehicle coordinate system. In order to verify the validity of this method, we installed a smart phone in the ‘Tuzhi’ self-driving car of Wuhan University and recorded more than 100km image data on the road in Wuhan. According to the result, we can calculate the positions of lane markers which are accurate enough for the self-driving car to run smoothly on the road.

scholarly journals A NOVEL APPROACH TO CAMERA CALIBRATION METHOD FOR SMART PHONES UNDER ROAD ENVIRONMENT

2016 ◽  
Vol XLI-B5 ◽  
pp. 49-54 ◽  
Author(s):  
Bijun Lee ◽  
Jian Zhou ◽  
Maosheng Ye ◽  
Yuan Guo
Keyword(s):  
Camera Calibration ◽  
Smart Phone ◽  
Warning System ◽  
Image Data ◽  
Calibration Method ◽  
Smart Phones ◽  
Driver Assistance Systems ◽  
The Road ◽  
Novel Approach ◽  
On The Road

Monocular vision-based lane departure warning system has been increasingly used in advanced driver assistance systems (ADAS). By the use of the lane mark detection and identification, we proposed an automatic and efficient camera calibration method for smart phones. At first, we can detect the lane marker feature in a perspective space and calculate edges of lane markers in image sequences. Second, because of the width of lane marker and road lane is fixed under the standard structural road environment, we can automatically build a transformation matrix between perspective space and 3D space and get a local map in vehicle coordinate system. In order to verify the validity of this method, we installed a smart phone in the ‘Tuzhi’ self-driving car of Wuhan University and recorded more than 100km image data on the road in Wuhan. According to the result, we can calculate the positions of lane markers which are accurate enough for the self-driving car to run smoothly on the road.

Improved Vision Based Driving Space Analysis by Condensation of Image Data

2012 ◽  
Vol 605-607 ◽  
pp. 2260-2264
Author(s):  
Yan Fen Mao ◽  
Hans Wiedmann ◽  
Ming Chen
Keyword(s):  
Image Data ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
The Road ◽  
Detection And Tracking ◽  
Detection And Identification ◽  
Diversity Sampling ◽  
Assistance Systems ◽  
On The Road ◽  
Improve Reliability

Sophisticated ADAS (Advanced Driver Assistance Systems) use vision based methods for detection and keeping track of ahead driving cars. With thus acquired data it is possible to implement e.g. following up functions to automatically keep equal distance to ahead driving vehicles or avoid collisions with obstacles ahead. Known vision based methods for detection and tracking of vehicles use its underneath shadow on the road. The main drawbacks of those methods are the detection and identification of a shadow belonging to a vehicle is neither reliable nor robust, and the thereto required processing of the camera images is very expensive concerning processing time. To improve reliability and detectability we propose here to use an approach which is different from the known methods a nonparametric one; to improve processing speed we propose to apply diversity-sampling to condense the image data before processing it.

scholarly journals Empirical Analysis of Safe Distance Calculation by the Stereoscopic Capturing and Processing of Images Through the Tailigator System

Sensors ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 5044
Author(s):  
Gerd Christian Krizek ◽  
Rene Hausleitner ◽  
Laura Böhme ◽  
Cristina Olaverri-Monreal
Keyword(s):  
Low Cost ◽  
Field Tests ◽  
Warning System ◽  
Collision Warning ◽  
The Road ◽  
Cost System ◽  
Straight Line ◽  
Real Value ◽  
On The Road ◽  
Forward Collision Warning

Driver disregard for the minimum safety distance increases the probability of rear-end collisions. In order to contribute to active safety on the road, we propose in this work a low-cost Forward Collision Warning system that captures and processes images. Using cameras located in the rear section of a leading vehicle, this system serves the purpose of discouraging tailgating behavior from the vehicle driving behind. We perform in this paper the pertinent field tests to assess system performance, focusing on the calculated distance from the processing of images and the error margins in a straight line, as well as in a curve. Based on the evaluation results, the current version of the Tailigator can be used at speeds up to 50 km per hour without any restrictions. The measurements showed similar characteristics both on the straight line and in the curve. At close distances, between 3 and 5 m, the values deviated from the real value. At average distances, around 10 to 15 m, the Tailigator achieved the best results. From distances higher than 20 m, the deviations increased steadily with the distance. We contribute to the state of the art with an innovative low-cost system to identify tailgating behavior and raise awareness, which works independently of the rear vehicle’s communication capabilities or equipment.

scholarly journals Design Method of ADAS for Urban Electric Vehicle Based on Virtual Prototyping

2018 ◽  
Vol 2018 ◽  
pp. 1-19 ◽  
Author(s):  
Katarzyna Jezierska-Krupa ◽  
Wojciech Skarka
Keyword(s):  
Design Method ◽  
Virtual Prototyping ◽  
Real Life ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Smart Power ◽  
The Road ◽  
Unique Method ◽  
On The Road ◽  
Positive Effect

Since 2012, the Smart Power Team has been actively participating in the Shell Eco-marathon, which is a worldwide competition. From the very beginning, the team has been working to increase driver’s safety on the road by developing Advanced Driver Assistance Systems. This paper presents unique method for designing ADAS systems in order to minimize the costs of the design phase and system implementation and, at the same time, to maximize the positive effect the system has on driver and vehicle safety. The described method is based on using virtual prototyping tool to simulate the system performance in real-life situations. This approach enabled an iterative design process, which resulted in reduction of errors with almost no prototyping and testing costs.

scholarly journals Proportional Swivel Headlight and Foglight Mechanism

2018 ◽  
Vol 5 (1) ◽  
pp. 55-60
Author(s):  
Prit Devendrakumar Shah ◽  
Ajay Patel ◽  
Manan Desai
Keyword(s):  
The Road ◽  
Novel Approach ◽  
Clear Vision ◽  
Optical Axes ◽  
On The Road

This paper describes the hardware of movable Headlight & Foglight system for vehicles. It has been found that the majority of accidents take place due to the invisibility of road at night & in fog. So, it becomes necessary that we get a clear vision during the night & in fog so as to avoid accidents. Therefore, the following research represents the rotation of headlight & foglight with the rotation of wheels. In this system used rack & pinion arrangement which give the drive to the optical axes on which headlight & foglight are mounted so when the links are moved with steering arm that gives predefined motion to headlight and foglight. Hence the light from the Headlight & Foglight focuses properly on the road, also while taking turn the driver coming from the opposite side can easily notice the upcoming vehicle & so the number of accidents is minimized. In this paper, we have defined a novel approach movement of foglight along with the headlight.

scholarly journals A Sensor Fused Rear Cross Traffic Detection System Using Transfer Learning

Sensors ◽  
2021 ◽  
Vol 21 (18) ◽  
pp. 6055
Author(s):  
Jungme Park ◽  
Wenchang Yu
Keyword(s):  
Processing Time ◽  
Detection System ◽  
Detection Accuracy ◽  
Driver Assistance Systems ◽  
The Road ◽  
Cross Traffic ◽  
Fast Processing ◽  
On The Road ◽  
Wide Angle Camera ◽  
Traffic Detection

Recent emerging automotive sensors and innovative technologies in Advanced Driver Assistance Systems (ADAS) increase the safety of driving a vehicle on the road. ADAS enhance road safety by providing early warning signals for drivers and controlling a vehicle accordingly to mitigate a collision. A Rear Cross Traffic (RCT) detection system is an important application of ADAS. Rear-end crashes are a frequently occurring type of collision, and approximately 29.7% of all crashes are rear-ended collisions. The RCT detection system detects obstacles at the rear while the car is backing up. In this paper, a robust sensor fused RCT detection system is proposed. By combining the information from two radars and a wide-angle camera, the locations of the target objects are identified using the proposed sensor fused algorithm. Then, the transferred Convolution Neural Network (CNN) model is used to classify the object type. The experiments show that the proposed sensor fused RCT detection system reduced the processing time 15.34 times faster than the camera-only system. The proposed system has achieved 96.42% accuracy. The experimental results demonstrate that the proposed sensor fused system has robust object detection accuracy and fast processing time, which is vital for deploying the ADAS system.

scholarly journals On the Application of Zone Flooding in a Traffic Warning System

2004 ◽  
Vol 33 (573) ◽  
Author(s):  
Lars Michael Kristensen ◽  
Kenneth-Daniel Nielsen
Keyword(s):  
Simulation Model ◽  
Warning System ◽  
Network Simulator ◽  
Font Size ◽  
Communication Infrastructure ◽  
State Information ◽  
The Road ◽  
System A ◽  
On The Road ◽  
Bounded Area

<span style="font-family: Times New Roman; font-size: x-small;"><span style="font-family: Times New Roman; font-size: x-small;"><p>The LIWAS Traffic Warning System aims at providing early warning to vehicles about slippery conditions on the road. The LIWAS system is currently under development and consists of two main parts: sensors for measuring and classifying the state of the road, and a communication infrastructure for distributing road-state information to vehicles. This paper concentrates on the communication infrastructure, and considers the application of zone flooding for implementing the distribution of road-state information. Zone flooding combines flooding and geocasting to distribute road-state information in a geographically bounded area. To evaluate the applicability of zone flooding in the LIWAS system, a simulation model has been created using the Network Simulator 2. The simulation model captures a representative road-scenario and has been used to evaluate several flooding protocols when used to implement zone flooding. The primary evaluationcriteria are the load on the network and the capability to warn other vehicles in time.</p></span></span>

Implementation of Lane Departure Warning System Based on Machine Vision

2013 ◽  
Vol 284-287 ◽  
pp. 2075-2079 ◽  
Author(s):  
Jia Shing Sheu ◽  
Hao Chu ◽  
Chun Chi Liu
Keyword(s):  
Machine Vision ◽  
Digital Camera ◽  
Warning System ◽  
Recognition System ◽  
Intelligent Transport System ◽  
Lane Departure Warning ◽  
The Road ◽  
Lane Departure ◽  
Moving Direction ◽  
On The Road

Purpose of this paper raise a vehicle lane departure warning system based on the machine vision. It does not need to use the parameters of the camera which do the road marking recognition system installed in the interior of the camera by algorithms. Regarding the time line of the intelligent transport system, it is to solve the various problems possibly arising from driving on the road. This system is mainly for the warning of the unexpected departure of vehicle. The method is to use the digital camera to capture continuous images and identify the vehicle moving direction by the detection of the left and right markings, as well as forecast the driving direction of the vehicle for the reference of vehicle departure warning. In this paper, the used algorithms include brightness adjustment, binarization, dilation, erosion, and edge detection image processing techniques.

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