scholarly journals The Rolling Out Of International Project SMART E263/E77 For Advanced Traffic Management

2021 ◽  
Vol 1202 (1) ◽  
pp. 012043
Author(s):  
Boriss Jelisejevs ◽  
Kristjan Duubas
Keyword(s):  
Traffic Control ◽  
Intelligent Transportation Systems ◽  
Traffic Management ◽  
Transportation Systems ◽  
Added Value ◽  
Traffic Information ◽  
Road Maintenance ◽  
The European Union ◽  
Road Transportation ◽  
Project Proposal

Abstract Intelligent transportation systems (ITS) provide significant added value to road transportation, making the related investments distinctively effective and long-lasting. Moreover, some ITS activities may be eligible for financial support of the European union (EU). That was the way how Estonian Transport Administration and Latvian State Roads worked on the project proposal “Smart corridor Tallinn-Tartu-Luhamaa-Riga E263/E77” (acronym – SMART E263/E77), which was approved by EU program Interreg Central Baltics as CB891 project. The project started on June 1, 2020, and its implementation will last till the end of 2022 according to quite challenging schedule. Project activities primarily include numerous installations or road telemetry and telematics devices (especially, variable message signs) for advanced traffic management to be supported by cross-border traffic plans and improvements of traffic control centers. Project target is to provide general travel time savings at least by 0.88% across the whole corridor, however for the motorway-type sections it should reach more than 5.5%. Expected project results will establish new and improve existing functions on the E263 and E77 road transport corridors, namely: traffic management adaptive to variable road conditions; gathering and dissemination of traffic information; decision-making support for road maintenance operations (especially in winter). This report will summarize the information on project progress with emphasis on traffic management considerations.

Road Traffic Congestion (TraCo) Estimation Using Multi-Layer Continuous Virtual Loop (MCVL)

2021 ◽  
Vol 17 (2) ◽  
pp. 46-71
Author(s):  
Manipriya Sankaranarayanan ◽  
Mala C. ◽  
Samson Mathew
Keyword(s):  
Intelligent Transportation Systems ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Road Traffic ◽  
Vehicle Detection ◽  
Transportation Systems ◽  
Traffic Information ◽  
Traffic Characteristics ◽  
Traffic Video ◽  
Virtual Loop

Any road traffic management application of intelligent transportation systems (ITS) requires traffic characteristics data such as vehicle density, speed, etc. This paper proposes a robust and novel vehicle detection framework known as multi-layer continuous virtual loop (MCVL) that uses computer vision techniques on road traffic video to estimate traffic characteristics. Estimations of traffic data such as speed, area occupancy and an exclusive spatial feature named as corner detail value (CDV) acquired using MCVL are proposed. Further, the estimation of traffic congestion (TraCo) level using these parameters is also presented. The performances of the entire framework and TraCo estimation are evaluated using several benchmark traffic video datasets and the results are presented. The results show that the improved accuracy in vehicle detection process using MCVL subsequently improves the precision of TraCo estimation. This also means that the proposed framework is well suited to applications that need traffic characteristics to update their traffic information system in real time.

Based on Data Fusion Intelligent Traffic Information Analysis and Optimization

2014 ◽  
Vol 568-570 ◽  
pp. 831-834
Author(s):  
Yuan Zhang Lu ◽  
Bing Zhang
Keyword(s):  
Data Fusion ◽  
Intelligent Transportation Systems ◽  
Traffic Management ◽  
Scientific Basis ◽  
Transportation Systems ◽  
Traffic Information ◽  
Information Analysis ◽  
Existing Problems ◽  
Attribute Data ◽  
Intelligent Analysis

In this paper, we propose an analysis refine scheme based on data fusion towards some existing problems in data analysis of intelligent transportation systems .This method constructed the data into a plurality of time-series according to the characteristics of each attribute data. Providing an objective scientific basis for dynamic traffic management through intelligent analysis of traffic information based on the gray advantage analysis among data and system model of Intelligent Traffic Information decision support and auxiliary decision analysis.

scholarly journals MuTraff: A Smart-City Multi-Map Traffic Routing Framework

Sensors ◽  
2019 ◽  
Vol 19 (24) ◽  
pp. 5342 ◽  
Author(s):  
Alvaro Paricio ◽  
Miguel Lopez-Carmona
Keyword(s):  
Traffic Control ◽  
Intelligent Transportation Systems ◽  
Traffic Management ◽  
Congestion Management ◽  
Transportation Systems ◽  
Urban Traffic ◽  
Reference Architecture ◽  
Control Center ◽  
Traffic Routing ◽  
Traffic Management System

Urban traffic routing is deemed to be a significant challenge in intelligent transportation systems. Existing implementations suffer from several intrinsic issues such as scalability in centralized systems, unnecessary complexity of mechanisms and communication in distributed systems, and lack of privacy. These imply force intensive computational tasks in the traffic control center, continuous communication in real-time with involved stakeholders which require drivers to reveal their location, origin, and destination of their trips. In this paper we present an innovative urban traffic routing framework and reference architecture (multimap traffic control architecture, MuTraff), which is based on the strategical generation and distribution of a set of traffic network maps (traffic weighted multimaps, TWM) to vehicle categories or fleets. Each map in a TWM map set has the same topology but a different distribution of link weights, which are computed by considering policies and constraints that may apply to different vehicle groups. MuTraff delivers a traffic management system (TMS), where a traffic control center generates and distributes maps, while routing computation is performed at the vehicles. We show how this balance between generation, distribution, and routing computation improves scalability, eases communication complexities, and solves former privacy issues. Our study presents case studies in a real city environment for (a) global congestion management using random maps; (b) congestion control on road incidents; and c) emergency fleets routing. We show that MuTraff is a promising foundation framework that is easy to deploy, and is compatible with other existing TMS frameworks.

802.11p-Based VANET Applications Improving Road Safety and Traffic Management

2016 ◽  
pp. 135-168
Author(s):  
Lambros Sarakis ◽  
Theofanis Orphanoudakis ◽  
Periklis Chatzimisios ◽  
Aristotelis Papantonis ◽  
Panagiotis Karkazis ◽  
...  
Keyword(s):  
Traffic Control ◽  
Intelligent Transportation Systems ◽  
Road Safety ◽  
Traffic Management ◽  
Vehicular Networks ◽  
Life Quality ◽  
Road Transport ◽  
Transportation Systems ◽  
Ieee 802.11P ◽  
Wireless Communication Protocol

In the last few years Intelligent Transportation Systems (ITS) based on wireless vehicular networks have been attracting interest, since they can contribute towards improving road transport safety and efficiency and ameliorate environmental conditions and life quality. In order to widely spread these technologies, standardization at each layer of the networking protocol stacks has to be done. Therefore, a suite of protocols along with the architecture for the wireless environments with vehicles has been developed and standardized. Both in the US as well as in Europe the selected wireless communication protocol has been the 802.11p protocol developed by the IEEE. In this chapter, we discuss the potential impact of ITS towards achieving the above targets of improving road safety and traffic control. We review the overall architecture and the protocol functionality and present in detail a number of applications that have been developed demonstrating selected use-cases on an 802.11p compliant system prototype. Specifically, we discuss the implementation of selected applications on the NEC's Linkbird-MX platform, which supports IEEE 802.11p based communications, showing how its functionality can be exploited to build efficient road safety and traffic management applications, and evaluate the performance of the system using an experimental testbed.

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>

Deriving Traffic-Performance Measures and Levels of Service from Second-Order Statistical Features of Spatiotemporal Traffic Contour Maps

2003 ◽  
Vol 1858 (1) ◽  
pp. 148-157 ◽  
Author(s):  
Sherif Ishak
Keyword(s):  
Intelligent Transportation Systems ◽  
Traffic Management ◽  
Performance Monitoring ◽  
Transportation Systems ◽  
Second Order ◽  
Level Of Service ◽  
Large Set ◽  
Contour Map ◽  
Contour Maps ◽  
Statistical Measures

Little information has been successfully extracted from the wealth of data collected by intelligent transportation systems. Such information is needed for the efficiency of operations and management functions of traffic-management centers. A new set of second-order statistical measures derived from texture characterization techniques in the field of digital image analysis is presented. The main objective is to improve the data-analysis tools used in performance-monitoring systems and assessment of level of service. The new measures can extract properties such as smoothness, homogeneity, regularity, and randomness in traffic operations directly from constructed spatiotemporal traffic contour maps. To avoid information redundancy, a correlation matrix was examined for nearly 14,000 15-min speed contour maps generated for a 3.4-mi freeway section over a period of 5 weekdays. The result was a set of three second-order measures: angular second moment, contrast, and entropy. Each measure was analyzed to examine its sensitivity to various traffic conditions, expressed by the overall speed mean of each contour map. The study also presented a tentative approach, similar to the conventional one used in the Highway Capacity Manual, to evaluate the level of service for each contour map. The new set of level-of-service criteria can be applied in real time by using a stand-alone module that was developed in the study. The module can be readily implemented online and allows traffic-management center operators to tune a large set of related parameters.

Smart Traffic Management for Collision Avoidance Using V2V

2021 ◽  
Vol 11 (1) ◽  
pp. 01-07
Author(s):  
V. Naren Thiruvalar ◽  
E. Vimal
Keyword(s):  
Intelligent Transportation Systems ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Emergency Situation ◽  
Transportation Systems ◽  
Pollution Monitoring ◽  
Inappropriate Use ◽  
V2v Communication ◽  
Use Of Resources ◽  
Smart Traffic

The main objective of this project is to connect the vehicles together and avoid accidents by using V2V Communication. The vehicles are to be connected together by means of DSRC algorithm which is used for transceiving alert messages among the connected vehicles, in case of any emergency situation such as accidents. The Vehicle-to-Vehicle (V2V) and Vehicle-to- Infrastructure (V2I) technologies are specific cases of IoT and key enablers for Intelligent Transportation Systems (ITS). V2V and V2I have been widely used to solve different problems associated with transportation in cities, in which the most important is traffic congestion. A high percentage of congestion is usually presented by the inappropriate use of resources in vehicular infrastructure. In addition, the integration of traffic congestion in decision making for vehicular traffic is a challenge due to its high dynamic behaviour. An increase in the infrastructure growth is a possible solution but turns out to be costly in terms of both time and effort. Various applications that target transport efficiency could make use of the vast information collected by vehicles: safety, traffic management, pollution monitoring, tourist information, etc.

An 802.11p Compliant System Prototype Supporting Road Safety and Traffic Management Applications

2014 ◽  
Vol 3 (1) ◽  
pp. 1-17 ◽  
Author(s):  
Helen C. Leligou ◽  
Periklis Chatzimisios ◽  
Lambros Sarakis ◽  
Theofanis Orphanoudakis ◽  
Panagiotis Karkazis ◽  
...  
Keyword(s):  
Intelligent Transportation Systems ◽  
Road Safety ◽  
Traffic Management ◽  
Life Quality ◽  
Road Transport ◽  
Transportation Systems ◽  
Ieee 802.11P ◽  
Practical Implementation ◽  
Communication Devices ◽  
The Right

During the last decades Intelligent Transportation Systems (ITS) have been attracting the interest of an increasing number of researchers, engineers and entrepreneurs, as well as citizens and civil authorities, since they can contribute towards improving road transport safety and efficiency and ameliorate environmental conditions and life quality. Emerging technologies yield miniaturized sensing, processing and communication devices that enable a high degree of integration and open the way for a large number of smart applications that can exploit automated fusion of information and enable efficient decisions by collecting, processing and communicating a large number of data in real-time. The cornerstone of these applications is the realization of an opportunistic wireless communication system between vehicles as well as between vehicles and infrastructure over which the right piece of information reaches the right location on time. In this paper, the authors present the design and implementation of representative safety and traffic management applications. Specifically the authors discuss the hardware and software requirements presenting a use case based on the NEC Linkbird-MX platform, which supports IEEE 802.11p based communications. The authors show how the functionality of IEEE 802.11p can be exploited to build efficient road safety and traffic management applications over mobile opportunistic systems and discuss practical implementation issues.

scholarly journals Analysis of Space-Time Variation of Passenger Flow and Commuting Characteristics of Residents Using Smart Card Data of Nanjing Metro

2019 ◽  
Vol 11 (18) ◽  
pp. 4989 ◽  
Author(s):  
Wei Yu ◽  
Hua Bai ◽  
Jun Chen ◽  
Xingchen Yan
Keyword(s):  
Intelligent Transportation Systems ◽  
Traffic Management ◽  
Rapid Development ◽  
Weather Conditions ◽  
Transportation Systems ◽  
Space Time ◽  
Smart Cards ◽  
The Sustainable Development ◽  
Passenger Flow ◽  
Challenges And Opportunities

The rapid development of cities has brought new challenges and opportunities to traditional traffic management. The usage of smart cards promotes the upgrading of intelligent transportation systems, and also produces considerable big data. As an important part of the urban comprehensive transportation system, Nanjing metro has more than 1 million inbound and outbound records of traffic smart cards used by residents every day. How to process these traffic data and present them visually is an urgent problem in modern traffic management. In this study, five working days with normal weather conditions in Nanjing were selected, and the swiping records of the smart cards were extracted, and the space–time characteristics were analyzed. In terms of time analysis, this research analyzed the 24-h fluctuation of daily average passenger flow, peak hour coefficient of passenger flow, 24-h fluctuation of passenger flow on different metro lines, passenger flow intensity on different metro lines and passenger flow comparison at different stations. In spatial analysis, this study uses thermodynamic charts to represent the inflow and outflow of passengers at different stations during early and evening peak periods. The analysis results and visualized images directly reflect the area where Nanjing metro congestion is located, and also shows the commuting characteristics of residents. It can solve the problem of urban congestion, carry out the rational layout of urban functional areas, and promote the sustainable development of people and cities.

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