scholarly journals The Use of Multi-Sensor Video Surveillance System to Assess the Capacity of the Road Network

2020 ◽  
Vol 21 (1) ◽  
pp. 15-31 ◽  
Author(s):  
Vladimir Shepelev ◽  
Sergei Aliukov ◽  
Kseniya Nikolskaya ◽  
Arkaprava Das ◽  
Ivan Slobodin
Keyword(s):  
Video Surveillance ◽  
Traffic Congestion ◽  
Surveillance Systems ◽  
Negative Consequences ◽  
Factors Affecting ◽  
Video Cameras ◽  
The Road ◽  
Scaling Methods ◽  
Additional Fuel Consumption ◽  
Additional Fuel

AbstractCurrently, in many cities around the world there is a significant increase in the number of vehicles, which leads to an aggravation of problems and contradictions in the road and transport system. This is especially true of traffic congestion, since the presence of the congestion leads to a number of negative consequences: an increase in travel time, additional fuel consumption and vehicle wear, stress and irritation of drivers and passengers, environmental poisoning and others. To solve the problem of congestion, it is necessary to have a reliable system for collecting information about the situation on the roads and a well-developed method for analyzing the collected information. The paper discusses the possibilities of collecting the required information using multi-touch video cameras and ways to improve them. A distinctive feature of this study is the registration of pedestrians crossing the road at the intersection. The aim of the work is to develop methods for collecting information using road sensor video surveillance systems in a traffic congestion and data processing using statistical methods such as: multiple regression analysis, cluster analysis, multidimensional scaling methods and others. The tasks were set: 1) to identify the most significant factors affecting the intensity of movement of vehicles at intersections in a congestion; 2) divide congestion into clusters with the identification of their characteristics; 3) to give a visual representation of multidimensional statistical information obtained with the help of multi-touch road video cameras.

scholarly journals The Capacity of the Road Network: Data Collection and Statistical Analysis of Traffic Characteristics

Energies ◽  
2020 ◽  
Vol 13 (7) ◽  
pp. 1765 ◽  
Author(s):  
Vladimir Shepelev ◽  
Sergei Aliukov ◽  
Kseniya Nikolskaya ◽  
Salavat Shabiev
Keyword(s):  
Data Collection ◽  
Road Traffic ◽  
Negative Consequences ◽  
The Road ◽  
Traffic Characteristics ◽  
Traffic Capacity ◽  
Traffic Data Collection ◽  
Fuzzy Logic Method ◽  
Additional Fuel Consumption ◽  
Additional Fuel

The possibilities of collecting the necessary information using multi-touch cameras and ways to improve road traffic data collection are considered. An increase in the number of vehicles leads to traffic jams, which in turn leads to an increase in travel time, additional fuel consumption and other negative consequences. To solve this problem, it is necessary to have a reliable information collection system and apply modern effective methods of processing the collected information. The technology considered in the article allows taking into account pedestrians crossing the intersection. The purpose of this article is to determine the most important traffic characteristics that affect the traffic capacity of the intersection, in other words, the actual number of passing cars. Throughput is taken as a dependent variable. Based on the results of the regression analysis, a model was developed to predict the intersection throughput taking into account the most important traffic characteristics. Besides, this model is based on the fuzzy logic method and using the Fuzzy TECH 5.81d Professional Edition computer program.

scholarly journals Comparison of Object Recognition Algorithms

2020 ◽  
pp. 21-25
Author(s):  
Gleb Popov ◽  
◽  
Tatiana Popova ◽  
Keyword(s):  
Object Recognition ◽  
Video Surveillance ◽  
Video Stream ◽  
Reference Image ◽  
Surveillance Systems ◽  
Small Object ◽  
Process Automation ◽  
Video Cameras ◽  
Recognition Algorithms ◽  
Special Points

Despite the increasing popularity of process automation, modern video surveillance systems still require constant human involvement to establish the fact of dangerous situations. But at present, systems are becoming more complex, this leads to an increase in threats and it is no longer possible for the operator to keep track of all emerging threats. In addition, in the field of video surveillance, tasks have been added that a person can no longer control just by watching video cameras. In this connection, you need to automate the process. Methods that provide maximum detection stability for small object movements, zoom changes, turning the object at a small angle, and changing lighting are based on describing the image at specific points. A special point is a point that has a number of key features that distinguish it from many other points in the image. Special points are the main characteristics of the object in the video surveillance system. The best object recognition algorithms based on this principle are the SURF and SIFT algorithms. These algorithms search for the direct occurrence of the reference image in relation to the observed one. The article discusses algorithms for detecting objects in an image based on the description of the image by special points. A comparison of SIFT and SURF algorithms, the analysis highlighted particular points in the recognition of each object, error analysis AI Node in identifying objects in the video stream.

scholarly journals Development of Road Congestion Index Based on Comprehensive Parameters

2020 ◽  
Vol 9 (9) ◽  
pp. 220-225
Keyword(s):  
Traffic Congestion ◽  
Heterogeneous Traffic ◽  
Main Concern ◽  
Affecting Factors ◽  
Factors Affecting ◽  
The Road ◽  
The People ◽  
Important Approach ◽  
On The Road ◽  
Congestion Index

Traffic congestion is a normal phenomenon associated with transportation on the road at the same time which is hinder motion and need extra time to reach destinations. Congestion is one of the problems involving road. Normally, network congestion occurs on land transport on roads. As demand approaches the capacity of a road or of the intersection along the road, extreme traffic congestion will sets in. When vehicles are fully stopped for periods of time, this is colloquially known as a traffic jam or snarl-up. Traffic congestion can lead to drivers becoming frustrated and engaging in road rage. In this study of developing congestion index for heterogeneous traffic at the road stretch from Navalur to Kelambakkam and Kelambakkam to Navalur, the study initially focuses on the identification of factors affecting traffic congestion, and finding the most vulnerable location for congestion by developing a congestion index based on speed and saturation degree, with these two important approach solution of each area is suggested. To calculate the traffic congestion index, a thorough literature review has been conducted and all the possible parameters are identified. A questionnaire was prepared with relevant factors affection congestion and distributed to the people, who are resident or frequent users. The most significant factors are considered for further study to avoid congestion. Lack of number of lanes, no pedestrian pathway, on road parking, location of toll were found to be the most affecting factors, so we suggest widening of roads, effective parking system , etc. It is also observed that particular area of Padur and Kelambakkam were the main concern of traffic congestion. This is confirmed both practically and theoretically with the help of the survey and the congestion index values.

The IFLA Global Vision Project in Zimbabwe: Towards a Unified Field Road Map for Libraries

Mousaion ◽  
2020 ◽  
Vol 37 (2) ◽  
Author(s):  
Collence Takaingenhamo Chisita ◽  
Nyarai Patience Chibanda
Keyword(s):  
Economic Transformation ◽  
International Federation ◽  
Access To Information ◽  
Factors Affecting ◽  
The Road ◽  
Unified Field ◽  
Road Map ◽  
Library Associations ◽  
Global Vision ◽  
Library Profession

The development of libraries in any country is critical for its socio-economic transformation especially during this 21st century era where access to information and knowledge underpins development. The International Federation of Library Associations and Institutions (IFLA) launched the Global Vision Project in 2017 as a way of strengthening library throughout the world. The project has seen over 190 countries participating worldwide. For most nations, especially those in the developing countries, this has indeed created platforms for strong and united library associations that are powering literate, informed and participative societies. A number of countries in Africa including Zimbabwe have taken the initiatives to participate in the IFLA Global Vision. This article seeks to examine the challenges and opportunities   for librarians in Zimbabwe in building a united library field. It will also scrutinize the road travelled by librarians in Zimbabwe in their pursuit of a vision to reposition their libraries on the global library landscape. The   article will also study the factors affecting the development of a unified library sector in Zimbabwe. It will also explore how the national professional association Zimbabwe Library Association (ZIMLA) can contribute towards a unified library profession through collaboration. The article also proposes a strategy to enhance cooperation among librarians in Zimbabwe.

scholarly journals Secure Video Surveillance Framework in Smart City

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4419
Author(s):  
Hao Li ◽  
Tianhao Xiezhang ◽  
Cheng Yang ◽  
Lianbing Deng ◽  
Peng Yi
Keyword(s):  
Video Surveillance ◽  
Smart City ◽  
Key Management ◽  
Surveillance System ◽  
Chinese Remainder Theorem ◽  
Smart Cities ◽  
Group Key Management ◽  
Video Surveillance System ◽  
Surveillance Systems ◽  
Key Update

In the construction process of smart cities, more and more video surveillance systems have been deployed for traffic, office buildings, shopping malls, and families. Thus, the security of video surveillance systems has attracted more attention. At present, many researchers focus on how to select the region of interest (RoI) accurately and then realize privacy protection in videos by selective encryption. However, relatively few researchers focus on building a security framework by analyzing the security of a video surveillance system from the system and data life cycle. By analyzing the surveillance video protection and the attack surface of a video surveillance system in a smart city, we constructed a secure surveillance framework in this manuscript. In the secure framework, a secure video surveillance model is proposed, and a secure authentication protocol that can resist man-in-the-middle attacks (MITM) and replay attacks is implemented. For the management of the video encryption key, we introduced the Chinese remainder theorem (CRT) on the basis of group key management to provide an efficient and secure key update. In addition, we built a decryption suite based on transparent encryption to ensure the security of the decryption environment. The security analysis proved that our system can guarantee the forward and backward security of the key update. In the experiment environment, the average decryption speed of our system can reach 91.47 Mb/s, which can meet the real-time requirement of practical applications.

scholarly journals Understanding Urban Commercial Vehicle Driver Behaviors and Decision Making

2021 ◽  
pp. 036119812110035
Author(s):  
Giacomo Dalla Chiara ◽  
Klaas Fiete Krutein ◽  
Andisheh Ranjbari ◽  
Anne Goodchild
Keyword(s):  
Commercial Vehicle ◽  
Operating Time ◽  
Common Belief ◽  
Policy Makers ◽  
Factors Affecting ◽  
Urban Freight ◽  
The Road ◽  
Commercial Drivers ◽  
The Common ◽  
Printed Materials

As e-commerce and urban deliveries spike, cities grapple with managing urban freight more actively. To manage urban deliveries effectively, city planners and policy makers need to better understand driver behaviors and the challenges they experience in making deliveries. In this study, we collected data on commercial vehicle (CV) driver behaviors by performing ridealongs with various logistics carriers. Ridealongs were performed in Seattle, Washington, covering a range of vehicles (cars, vans, and trucks), goods (parcels, mail, beverages, and printed materials), and customer types (residential, office, large and small retail). Observers collected qualitative observations and quantitative data on trip and dwell times, while also tracking vehicles with global positioning system devices. The results showed that, on average, urban CVs spent 80% of their daily operating time parked. The study also found that, unlike the common belief, drivers (especially those operating heavier vehicles) parked in authorized parking locations, with only less than 5% of stops occurring in the travel lane. Dwell times associated with authorized parking locations were significantly longer than those of other parking locations, and mail and heavy goods deliveries generally had longer dwell times. We also identified three main criteria CV drivers used for choosing a parking location: avoiding unsafe maneuvers, minimizing conflicts with other users of the road, and competition with other commercial drivers. The results provide estimates for trip times, dwell times, and parking choice types, as well as insights into why those decisions are made and the factors affecting driver choices.

Sign in / Sign up

Export Citation Format

Share Document