The Mode of Exploration and Practice with Modern Corporate Governance for Administrative Service of Road Traffic Management in Public Security Department Based on the Big Data

CICTP 2020 ◽  
2020 ◽  
Author(s):  
Jianguo Gong ◽  
Xiucheng Guo ◽  
Shuai Dai ◽  
Yujuan Zhao
Keyword(s):  
Corporate Governance ◽  
Big Data ◽  
Traffic Management ◽  
Road Traffic ◽  
Public Security ◽  
Administrative Service

scholarly journals Contribution of Collaborative Filtering Approach on Environmental Big Data Analytics Context

2021 ◽  
Vol 319 ◽  
pp. 01082
Author(s):  
Abarou Salma ◽  
El Abderrahmani Abdellatif ◽  
Satori Khalid
Keyword(s):  
Big Data ◽  
Collaborative Filtering ◽  
Traffic Management ◽  
Data Analytics ◽  
Road Traffic ◽  
Big Data Analytics ◽  
Environmental Damage ◽  
Internet Users ◽  
To Come ◽  
Filtering Approach

In recent years and following the spread of internet using, the way of life in our society as well as the management of the main production sectors have changed towards digitalization (E-Commerce, E-Surgery, road traffic management, etc.) to minimize the. This change challenged researchers and organizations to come up with solutions to manage, maintain, classify and make the best decision from the gigantic flows of data created daily while reducing environmental Damage (Consumption of Energical resources….), From which was born the Collaborative filtering approach which facilitate decision making based on the experience feedback of Internet users. This approach is used generally the big Data Analytics Algorithm to predict and classify data

scholarly journals Extracting Road Traffic Volume in the City before and during covid-19 through Video Remote Sensing

2021 ◽  
Vol 13 (12) ◽  
pp. 2329
Author(s):  
Elżbieta Macioszek ◽  
Agata Kurek
Keyword(s):  
Travel Behavior ◽  
Traffic Management ◽  
Road Traffic ◽  
Traffic Volume ◽  
The Road ◽  
Traffic Characteristics ◽  
Annual Average Daily Traffic ◽  
On The Road ◽  
The Impact ◽  
The City

Continuous, automatic measurements of road traffic volume allow the obtaining of information on daily, weekly or seasonal fluctuations in road traffic volume. They are the basis for calculating the annual average daily traffic volume, obtaining information about the relevant traffic volume, or calculating indicators for converting traffic volume from short-term measurements to average daily traffic volume. The covid-19 pandemic has contributed to extensive social and economic anomalies worldwide. In addition to the health consequences, the impact on travel behavior on the transport network was also sudden, extensive, and unpredictable. Changes in the transport behavior resulted in different values of traffic volume on the road and street network than before. The article presents road traffic volume analysis in the city before and during the restrictions related to covid-19. Selected traffic characteristics were compared for 2019 and 2020. This analysis made it possible to characterize the daily, weekly and annual variability of traffic volume in 2019 and 2020. Moreover, the article attempts to estimate daily traffic patterns at particular stages of the pandemic. These types of patterns were also constructed for the weeks in 2019 corresponding to these stages of the pandemic. Daily traffic volume distributions in 2020 were compared with the corresponding ones in 2019. The obtained results may be useful in terms of planning operational and strategic activities in the field of traffic management in the city and management in subsequent stages of a pandemic or subsequent pandemics.

scholarly journals Road Traffic Congestion Management Based on a Search-Allocation Approach

2017 ◽  
Vol 18 (1) ◽  
pp. 25-33 ◽  
Author(s):  
Jamal Raiyn
Keyword(s):  
Travel Time ◽  
Real Time ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Road Traffic ◽  
Smart Cities ◽  
Self Regulation ◽  
Congestion Management ◽  
Shortest Route ◽  
Road Traffic Congestion

Abstract This paper introduces a new scheme for road traffic management in smart cities, aimed at reducing road traffic congestion. The scheme is based on a combination of searching, updating, and allocation techniques (SUA). An SUA approach is proposed to reduce the processing time for forecasting the conditions of all road sections in real-time, which is typically considerable and complex. It searches for the shortest route based on historical observations, then computes travel time forecasts based on vehicular location in real-time. Using updated information, which includes travel time forecasts and accident forecasts, the vehicle is allocated the appropriate section. The novelty of the SUA scheme lies in its updating of vehicles in every time to reduce traffic congestion. Furthermore, the SUA approach supports autonomy and management by self-regulation, which recommends its use in smart cities that support internet of things (IoT) technologies.

ORGANIZATION OF ROAD TRAFFIC TAKING INTO ACCOUNT ELECTRIC ROUTE PASSENGER TRANSPORT

2021 ◽  
Vol 2 (65) ◽  
pp. 66-77
Author(s):  
Denis V. Kapsky ◽  
◽  
Sergey S. Semchenkov ◽  
Evgeny N. Kot ◽  
◽  
...  
Keyword(s):  
Traffic Management ◽  
Road Traffic ◽  
Rapid Development ◽  
Living Environment ◽  
Transport Sector ◽  
Passenger Transport ◽  
Wide Range ◽  
Practical Development ◽  
The Republic ◽  
Conducting Research

The rapid development of the transport sector leads not only to positive changes in the life of cities and towns, to an increase in convenience and comfort for residents, but also worsens the ecology and their living environment. The “profitable-safe” dilemma can be solved by the approach of environmentally oriented selection of the type of route passenger transport and decisionmaking in favor of electric route passenger transport. The article discusses the types of such transport on the example of the experience of their use in the Republic of Belarus. The classification and systematization developed by the authors are presented with subsequent recommendations for its application. On the basis of the results of the authors’ research, the issues of interaction of rail and non-rail route vehicles with an electric drive with the organization of road traffic are separately considered. The presented materials can be useful to a wide range of readers, as well as to specialists conducting research and practical development in the field of electrically powered route vehicles and traffic management.

Towards Intelligent Road Traffic Management over Weighted Large Graphs Hybrid Meta-heuristic-Based Approach

2022 ◽  
Vol 24 (3) ◽  
pp. 0-0
Keyword(s):  
Traffic Management ◽  
Large Scale ◽  
Road Traffic ◽  
Optimization Technique ◽  
Shortest Paths ◽  
Hybrid Genetic Algorithm ◽  
Optimal Solution ◽  
Computation Time ◽  
Exact Algorithm ◽  
On The Road

This paper introduces a new approach of hybrid meta-heuristics based optimization technique for decreasing the computation time of the shortest paths algorithm. The problem of finding the shortest paths is a combinatorial optimization problem which has been well studied from various fields. The number of vehicles on the road has increased incredibly. Therefore, traffic management has become a major problem. We study the traffic network in large scale routing problems as a field of application. The meta-heuristic we propose introduces new hybrid genetic algorithm named IOGA. The problem consists of finding the k optimal paths that minimizes a metric such as distance, time, etc. Testing was performed using an exact algorithm and meta-heuristic algorithm on random generated network instances. Experimental analyses demonstrate the efficiency of our proposed approach in terms of runtime and quality of the result. Empirical results obtained show that the proposed algorithm outperforms some of the existing technique in term of the optimal solution in every generation.

Telecommunications- and Information Technology–Inspired Analyses: Review of an Intelligent Transportation Systems Experience

2017 ◽  
Vol 2658 (1) ◽  
pp. 44-55 ◽  
Author(s):  
Yupo Chan
Keyword(s):  
Information Technology ◽  
Big Data ◽  
Real Time ◽  
Traffic Management ◽  
Transportation Systems ◽  
Lessons Learned ◽  
Connected Vehicles ◽  
Ongoing Research ◽  
Real Time Information ◽  
Time Information

This paper reviews both the author’s experience with managing highway network traffic on a real-time basis and the ongoing research into harnessing the potential of telecommunications and information technology (IT). On the basis of the lessons learned, this paper speculates about how telecommunications and IT capabilities can respond to current and future developments in traffic management. Issues arising from disruptive telecommunications technologies include the ready availability of real-time information, the crowdsourcing of information, the challenges of big data, and the need for information quality. Issues arising from transportation technologies include autonomous vehicles and connected vehicles and new taxi-like car- and bikesharing. Illustrations are drawn from the following core functions of a traffic management center: ( a) detecting and resolving an incident (possibly through crowdsourcing), ( b) monitoring and forecasting traffic (possibly through connected vehicles serving as sensors), ( c) advising motorists about routing alternatives (possibly through real-time information), and ( d) configuring traffic control strategies and tactics (possibly though big data). The conclusion drawn is that agility is the key to success in an ever-evolving technological scene. The solid guiding principle remains innovative and rigorous analytical procedures that build on the state of the art in the field, including both hard and soft technologies. The biggest modeling and simulation challenge remains the unknown, including such rapidly emerging trends as the Internet of things and the smart city.

scholarly journals Mobile Road Traffic Management System Using Weighted Sensor

2017 ◽  
Vol 11 (5) ◽  
pp. 147 ◽  
Author(s):  
Solomon Adegbenro Akinboro ◽  
Johnson A Adeyiga ◽  
Adebayo Omotosho ◽  
Akinwale O Akinwumi
Keyword(s):  
Real Time ◽  
Traffic Control ◽  
Urban Areas ◽  
Traffic Management ◽  
Management System ◽  
Road Traffic ◽  
Traffic Information ◽  
Traffic Light ◽  
Real Time Traffic ◽  
Traffic Management System

<p><strong>Vehicular traffic is continuously increasing around the world, especially in urban areas, and the resulting congestion ha</strong><strong>s</strong><strong> be</strong><strong>come</strong><strong> a major concern to automobile users. The popular static electric traffic light controlling system can no longer sufficiently manage the traffic volume in large cities where real time traffic control is paramount to deciding best route. The proposed mobile traffic management system provides users with traffic information on congested roads using weighted sensors. A prototype of the system was implemented using Java SE Development Kit 8 and Google map. The model </strong><strong>was</strong><strong> simulated and the performance was </strong><strong>assessed</strong><strong> using response time, delay and throughput. Results showed that</strong><strong>,</strong><strong> mobile devices are capable of assisting road users’ in faster decision making by providing real-time traffic information and recommending alternative routes.</strong></p>

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