Traffic Monitoring Technique Based on Kalman Filtering and Multi-Feature Matching

2014 ◽  
Vol 701-702 ◽  
pp. 390-394
Author(s):  
Lan Ying Liu
Keyword(s):  
Kalman Filter ◽  
Feature Matching ◽  
Target Position ◽  
Traffic Monitoring ◽  
Detection Accuracy ◽  
Sift Algorithm ◽  
The Road ◽  
Difference Image ◽  
Sift Features ◽  
The Cost

Traffic monitoring system based on image processing technology,which can reflect the information of traffic .The cost of use and maintenance is relatively low ,which can be widely applied to monitor complex area and crossing the road. In this paper, a new algorithm for traffic monitoring had be proposed, which combined the SIFT algorithm and kalman filter. Firstly, extracting SIFT targets based on the Pyramid of Gauss difference image, target position was doped out by kalman filter and builded the adapted window. Finally, the SIFT algorithm was used to extract target features and matching them. According to the next kalman location set prediction area, in this area combinated with target center and SIFT features, then selected the best objection for accurate tracking,acquire traffic parameters with traffic fiow and average speed.Experimental results show that detection accuracy is more than 91%,the method has strong robustness and realtime。

scholarly journals Acoustic Detector of Road Vehicles Based on Sound Intensity

Sensors ◽  
2021 ◽  
Vol 21 (23) ◽  
pp. 7781
Author(s):  
Grzegorz Szwoch ◽  
Józef Kotus
Keyword(s):  
Low Cost ◽  
Sound Intensity ◽  
Traffic Monitoring ◽  
Detection Accuracy ◽  
Road Vehicles ◽  
Moving Vehicle ◽  
The Road ◽  
Acoustic Detector ◽  
Direction Of Movement ◽  
Made In

A method of detecting and counting road vehicles using an acoustic sensor placed by the road is presented. The sensor measures sound intensity in two directions: parallel and perpendicular to the road. The sound intensity analysis performs acoustic event detection. A normalized position of the sound source is tracked and used to determine if the detected event is related to a moving vehicle and to establish the direction of movement. The algorithm was tested on a continuous 24-h recording made in real-world conditions. The overall results were: recall 0.95, precision 0.95, F-score 0.95. In the analysis of one-hour slots, the worst results obtained in dense traffic were: recall 0.9, precision 0.93, F-score 0.91. The proposed method is intended for application in a network of traffic monitoring sensors, such as a smart city system. Its advantages include using a small, low cost and passive sensor, low algorithm complexity, and satisfactory detection accuracy.

scholarly journals Automatic Roadway Features Detection with Oriented Object Detection

2021 ◽  
Vol 11 (8) ◽  
pp. 3531
Author(s):  
Hesham M. Eraqi ◽  
Karim Soliman ◽  
Dalia Said ◽  
Omar R. Elezaby ◽  
Mohamed N. Moustafa ◽  
...  
Keyword(s):  
Object Detection ◽  
Safety Evaluation ◽  
Autonomous Driving ◽  
Detection Accuracy ◽  
The Road ◽  
Detection Model ◽  
Detection Approach ◽  
Roadway Safety ◽  
Safety Features ◽  
Oriented Object

Extensive research efforts have been devoted to identify and improve roadway features that impact safety. Maintaining roadway safety features relies on costly manual operations of regular road surveying and data analysis. This paper introduces an automatic roadway safety features detection approach, which harnesses the potential of artificial intelligence (AI) computer vision to make the process more efficient and less costly. Given a front-facing camera and a global positioning system (GPS) sensor, the proposed system automatically evaluates ten roadway safety features. The system is composed of an oriented (or rotated) object detection model, which solves an orientation encoding discontinuity problem to improve detection accuracy, and a rule-based roadway safety evaluation module. To train and validate the proposed model, a fully-annotated dataset for roadway safety features extraction was collected covering 473 km of roads. The proposed method baseline results are found encouraging when compared to the state-of-the-art models. Different oriented object detection strategies are presented and discussed, and the developed model resulted in improving the mean average precision (mAP) by 16.9% when compared with the literature. The roadway safety feature average prediction accuracy is 84.39% and ranges between 91.11% and 63.12%. The introduced model can pervasively enable/disable autonomous driving (AD) based on safety features of the road; and empower connected vehicles (CV) to send and receive estimated safety features, alerting drivers about black spots or relatively less-safe segments or roads.

scholarly journals Anomaly Detection Using Deep Neural Network for IoT Architecture

2021 ◽  
Vol 11 (15) ◽  
pp. 7050
Author(s):  
Zeeshan Ahmad ◽  
Adnan Shahid Khan ◽  
Kashif Nisar ◽  
Iram Haider ◽  
Rosilah Hassan ◽  
...  
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Anomaly Detection ◽  
Deep Neural Network ◽  
Detection System ◽  
Traffic Monitoring ◽  
Detection Accuracy ◽  
Learning Models ◽  
Prime Concern ◽  
Entry Points

The revolutionary idea of the internet of things (IoT) architecture has gained enormous popularity over the last decade, resulting in an exponential growth in the IoT networks, connected devices, and the data processed therein. Since IoT devices generate and exchange sensitive data over the traditional internet, security has become a prime concern due to the generation of zero-day cyberattacks. A network-based intrusion detection system (NIDS) can provide the much-needed efficient security solution to the IoT network by protecting the network entry points through constant network traffic monitoring. Recent NIDS have a high false alarm rate (FAR) in detecting the anomalies, including the novel and zero-day anomalies. This paper proposes an efficient anomaly detection mechanism using mutual information (MI), considering a deep neural network (DNN) for an IoT network. A comparative analysis of different deep-learning models such as DNN, Convolutional Neural Network, Recurrent Neural Network, and its different variants, such as Gated Recurrent Unit and Long Short-term Memory is performed considering the IoT-Botnet 2020 dataset. Experimental results show the improvement of 0.57–2.6% in terms of the model’s accuracy, while at the same time reducing the FAR by 0.23–7.98% to show the effectiveness of the DNN-based NIDS model compared to the well-known deep learning models. It was also observed that using only the 16–35 best numerical features selected using MI instead of 80 features of the dataset result in almost negligible degradation in the model’s performance but helped in decreasing the overall model’s complexity. In addition, the overall accuracy of the DL-based models is further improved by almost 0.99–3.45% in terms of the detection accuracy considering only the top five categorical and numerical features.

FPGA and ASIC implementation of the algorithm for traffic monitoring in urban areas

2011 ◽  
Vol 59 (2) ◽  
pp. 137-140 ◽  
Author(s):  
S. Szczepański ◽  
M. Wöjcikowski ◽  
B. Pankiewicz ◽  
M. KŁosowski ◽  
R. Żaglewski
Keyword(s):  
Urban Areas ◽  
Traffic Monitoring ◽  
Detection Algorithm ◽  
Frame Rate ◽  
Integrated Sensor ◽  
The Road ◽  
Moving Vehicles ◽  
Direction Of Movement ◽  
Account Due ◽  
Selection Of

FPGA and ASIC implementation of the algorithm for traffic monitoring in urban areas This paper describes the idea and the implementation of the image detection algorithm, that can be used in integrated sensor networks for environment and traffic monitoring in urban areas. The algorithm is dedicated to the extraction of moving vehicles from real-time camera images for the evaluation of traffic parameters, such as the number of vehicles, their direction of movement and their approximate speed. The authors, apart from the careful selection of particular steps of the algorithm towards hardware implementation, also proposed novel improvements, resulting in increasing the robustness and the efficiency. A single, stationary, monochrome camera is used, simple shadow and highlight elimination is performed. The occlusions are not taken into account, due to placing the camera at a location high above the road. The algorithm is designed and implemented in pipelined hardware, therefore high frame-rate efficiency has been achieved. The algorithm has been implemented and tested in FPGA and ASIC.

Determining Minimum Contract Time for Highway Projects

2000 ◽  
Vol 1712 (1) ◽  
pp. 196-201 ◽  
Author(s):  
Jin-Fang Shr ◽  
Benjamin P. Thompson ◽  
Jeffrey S. Russell ◽  
Bin Ran ◽  
H. Ping Tserng
Keyword(s):  
Low Cost ◽  
Road User ◽  
User Cost ◽  
Time Curve ◽  
Highway Projects ◽  
The Road ◽  
State Highway ◽  
Florida Department ◽  
The Cost ◽  
State Highway Agencies

An increasing number of state highway agencies (SHAs) are using A (cost) + B (time cost) bidding ( A + B bidding) for highway construction. The A + B bidding concept is designed to shorten the total contract time by allowing each contractor to bid the number of days in which the work can be accomplished, in addition to the traditional cost bid. The SHA is then presented with the problem of determining a reasonable range of contract time submitted by the bidders. Most SHAs do not currently restrict the range of B. However, several problems may arise from an unrestricted range of B. First, if no minimum is set for B, a bidder may inflate the cost bid and submit an unreasonably low B, using the excess cost bid to cover the disincentives charged for exceeding the time bid. Second, if no maximum is set for B, then a bidder with a high B and a low-cost bid may be awarded the job and make an unreasonable amount of money from incentive payments. This study develops a quantified model of the price-time bidding contract. A construction cost-versus-time curve is developed from Florida Department of Transportation (DOT) data. The contractor’s price-versus-time curve is then combined with the road-user cost to determine the optimum lower limit to be set on B. Finally, several projects completed by the Florida DOT will be used to illustrate this model.

Medical Image Feature Matching Based on Wavelet Transform and SIFT Algorithm

2011 ◽  
Vol 65 ◽  
pp. 497-502
Author(s):  
Yan Wei Wang ◽  
Hui Li Yu
Keyword(s):  
Wavelet Transform ◽  
Wavelet Transforms ◽  
Medical Image ◽  
Feature Matching ◽  
Image Feature ◽  
Scale Invariant ◽  
Sift Algorithm ◽  
Matching Algorithm ◽  
Invariant Feature ◽  
Scale Invariant Feature

A feature matching algorithm based on wavelet transform and SIFT is proposed in this paper, Firstly, Biorthogonal wavelet transforms algorithm is used for medical image to delaminating, and restoration the processed image. Then the SIFT (Scale Invariant Feature Transform) applied in this paper to abstracting key point. Experimental results show that our algorithm compares favorably in high-compressive ratio, the rapid matching speed and low storage of the image, especially for the tilt and rotation conditions.

Road Detection Based on Edge Feature with GAC Model in Aerial Image

2021 ◽  
Author(s):  
Linying Zhou ◽  
Zhou Zhou ◽  
Hang Ning
Keyword(s):  
Transformation Method ◽  
Aerial Images ◽  
Aerial Image ◽  
Initial Contour ◽  
Detection Accuracy ◽  
Road Detection ◽  
Canny Operator ◽  
The Road ◽  
Gradient Magnitude ◽  
Edge Feature

Road detection from aerial images still is a challenging task since it is heavily influenced by spectral reflectance, shadows and occlusions. In order to increase the road detection accuracy, a proposed method for road detection by GAC model with edge feature extraction and segmentation is studied in this paper. First, edge feature can be extracted using the proposed gradient magnitude with Canny operator. Then, a reconstructed gradient map is applied in watershed transformation method, which is segmented for the next initial contour. Last, with the combination of edge feature and initial contour, the boundary stopping function is applied in the GAC model. The road boundary result can be accomplished finally. Experimental results show, by comparing with other methods in [Formula: see text]-measure system, that the proposed method can achieve satisfying results.

Theoretical and methodological approaches to the calculation of planned costs for maintenance of service vehicles of the road works customer

2021 ◽  
Vol 2021 (23) ◽  
pp. 20-30
Author(s):  
Taras Pechonchyk ◽  
◽  
Vitaliy Ivanchenko ◽  
Keyword(s):  
Customer Service ◽  
Planning Process ◽  
Spare Parts ◽  
Cost Estimates ◽  
The Road ◽  
Fleet Composition ◽  
Cost Planning ◽  
Methodological Approaches ◽  
The Cost ◽  
Service Vehicles

AbstractIntroduction. Effective management of road indstry is particularly important in conditions of limited funding, as it is not possible to provide adequate funding of the economic entity that has the functions of a customer service. The cost of the customer service maintenance depends directly on the compliance with applicable regulations for these works cost determination. One of the aspects that form a considerable part of the costs of customer service is the maintenance of service vehicles.Problem Statement. Road services in the regions (hereinafter RSR) are the recipients and managers of the funds from the State Budget of Ukraine that are directed for the development and maintenance of public roads of state importance, being as well the asset holders of these roads. To perform their functions, the RSR have vehicles on their balance, the use of which involves a number of costs, including fuel and lubricants, repair, maintenance, replacement of tires, etc. The most important of the steps involved in setting the costs of vehicle maintenance is the process of cost planning. Planning has to be based on the structure of the vehicle fleet (own or leased), functional responsibilities and scope of road works.Planning is carried out for vehicles on the balance of the RSR, as well as for leased vehicles. In the case of leasing, the costs mentioned above are added by the vehicles leasing costs. These costs must be forecasted, justified and performed within the approved cost estimates of the customer service expenses.Purpose. The purpose of the article is to highlight the theoretical and methodological approaches to the calculation of planned costs for the maintenance of service vehicles of the road works customer.Materials and methods. Dialectical methods of knowledge, such as analysis and synthesis of fleet composition characteristics and approaches to cost planning methods, as well as induction, were used in writing the article to explore some aspects of the process of calculating the planned cost of maintenance of the road works customer's service vehicles.Results. The study highlights and describes the main approaches to the calculation of planned costs for the maintenance of service vehicles of the road works customer. The methodology of calculation of planned costs for the maintenance of service vehicles is explored.Conclusions. The introduction of a clear methodology and analytical toolkit for calculating all necessary expenditure items for the maintenance of the road works customer's vehicles in the cost planning process will establish the implementation of a clear mechanism for calculating the planned costs of maintenance of the road works customer's vehicles. It will also provide an automated information-analytical complex for planning of cost estimates, with information entry and reporting in standard forms and possibility of prompt response to changes in fleet composition, needs for spare parts, repairs or other expenses for the maintenance of service vehicles and making changes in cost estimates.Keywords: motor vehicles, costs, cost planning, customer service, maintenance of service vehicles

Review of recent developments on improvement of estimated regulatory documentation for road works

2021 ◽  
Vol 2021 (23) ◽  
pp. 31-42
Author(s):  
Anatolii Tsynka ◽  
◽  
Andrii Hrinchuk ◽  
Ivan Rakovych ◽  
◽  
...  
Keyword(s):  
Work Performance ◽  
New Technologies ◽  
Operation Time ◽  
Road Construction ◽  
Labor Costs ◽  
The Road ◽  
Regulatory Documents ◽  
Road Work ◽  
Investment Process ◽  
The Cost

Introduction. In the modern conditions of the pricing system in the construction of Ukraine, the key value have the estimated norms, which are presented in separate collections, the main purpose of which is to determine the standard quantity of resources required to perform a particular type of work as a basis for the transition to the cost indicators. In order to determine the cost of road work objectively and accurately, it is essential that the indicators of estimated norms meet the requirements of regulatory documents and modern methods of execution of road works.Problematics. In connection with the active improvement of the regulatory base of the road construction industry, permanent upgrade of road organizations technique fleet, the introduction of new technologies and materials in construction and operation of roads, improving the methods of work there is a discrepancy between the existing resource element of estimated norms and the actual conditions of work in terms of built-up labor costs, the operation time of machines and mechanisms and the range of materials. Accordingly, it affects the reliability and accuracy of determining the cost of road works.Purpose. Improvement and harmonization with actual working conditions and requirements of regulatory documents of industry regulatory and estimate base of resource elementary estimated norms for work performed during construction, reconstruction, repair and operational maintenance of roads and bridges to ensure reliable and valid technical, economic and estimated calculations.Materials and methods. During work performance the analysis of the regulatory documentation, establishing the requirements to the technology of road works and materials has been carried out. A number of chronometric observations with the measurement of time of road works in full-scale conditions was carried out. The obtained data were summarized, averaged and on their basis the indicators of the resource element of the estimated norms were estimated.Results. A review of the main amendments and additions, which came into force after the approval of Amendment No 2 SOU 42.1-37641918-035:2018 [1] and Amendment No 2 SOU 42.1-37641918-071:2018 [2], which were developed to improve the regulatory-estimate base for the calculation of road works, taking into account the requirements and provisions of existing regulatory documents taking into account the current state of scientific and technological progress in the road sector.Conclusions. The above analysis of the amendments that came into force with the approval of [1]. and [2] will systematize the innovations provided by the requirements of current regulatory documents on the calculation of the cost of road works and the development of relevant documents at all stages of the investment process, planning and organization of road works, as well as the writing-off of material resources. Review and systematization of recent improvements in the estimated regulatory documents for road works will provide an opportunity to optimally plan the use of available material, labor and financial resources, often limited.Keywords: public road, operational maintenance, investment documentation, overhaul and current repairs, machine, mechanism, regulatory document, resource element estimate norm, Standard of Organization of Ukraine.

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