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.

scholarly journals Collaborative and Infrastructure-less Vehicular Traffic Rerouting for Intelligent Transportation Systems

2020 ◽  
Author(s):  
Ademar Takeo Akabane ◽  
Edmundo Roberto Mauro Madeira ◽  
Leandro Aparecido Villas
Keyword(s):  
Intelligent Transportation Systems ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Management System ◽  
Cost Effective ◽  
Intelligent Transportation ◽  
Good Alternative ◽  
Transportation Systems ◽  
Vehicular Traffic ◽  
Traffic Management System

This extended abstract provides an at-a-glance view of the main contributions of my Ph.D. work. The work aims to investigate and develop cutting-edge an infrastructure-less vehicular traffic management system in order to minimize vehicular traffic congestion and advance the state-of-the-art in intelligent transportation systems. The proposed solutions were widely compared with other literature solutions on different performance evaluation metrics. The evaluation results show that the proposed vehicle traffic management system is efficient, scalable, and cost-effective, which may be a good alternative to mitigate urban mobility problems.

scholarly journals A NOVEL DEEP LEARNING BASED METHOD FOR DETECTION AND COUNTING OF VEHICLES IN URBAN TRAFFIC SURVEILLANCE SYSTEMS

2021 ◽  
Vol XLIII-B2-2021 ◽  
pp. 793-800
Author(s):  
J. J. Majin ◽  
Y. M. Valencia ◽  
M. E. Stivanello ◽  
M. R. Stemmer ◽  
J. D. Salazar
Keyword(s):  
Deep Learning ◽  
Object Detection ◽  
Intelligent Transportation Systems ◽  
Traffic Management ◽  
Management Strategies ◽  
Transportation Systems ◽  
Urban Traffic ◽  
Surveillance Systems ◽  
Real Time Processing ◽  
Detection Model

Abstract. In intelligent transportation systems (ITS), it is essential to obtain reliable statistics of the vehicular flow in order to create urban traffic management strategies. These systems have benefited from the increase in computational resources and the improvement of image processing methods, especially in object detection based on deep learning. This paper proposes a method for vehicle counting composed of three stages: object detection, tracking and trajectory processing. In order to select the detection model with the best trade-off between accuracy and speed, the following one-stage detection models were compared: SSD512, CenterNet, Efficiedet-D0 and YOLO family models (v2, v3 and v4). Experimental results conducted on the benchmark dataset show that the best rates among the detection models were obtained using YOLOv4 with mAP = 87% and a processing speed of 18 FPS. On the other hand, the accuracy obtained in the proposed counting method was 94% with a real-time processing rate lower than 1.9.

Smart Traffic Management System for Anticipating Unexpected Road Incidents in Intelligent Transportation Systems

2018 ◽  
Vol 10 (4) ◽  
pp. 67-82
Author(s):  
Abdelatif Sahraoui ◽  
Derdour Makhlouf ◽  
Philippe Roose
Keyword(s):  
Predictive Model ◽  
Intelligent Transportation Systems ◽  
Traffic Management ◽  
Management System ◽  
Statistical Significance ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Practical Case ◽  
Traffic Management System ◽  
Smart Traffic

This article describes how anticipating unforeseen road events reveal a serious problem in intelligent transportation systems. Due to the diversity of causes, road incidents do not require regular traffic conditions and accurate prediction of these incidents in real-time becomes a complicated task not defined so far. In this article, a smart traffic management system based cloud-assisted service is proposed to preserve the traffic safety by controlling the road segments and predicts the probability of incoming incidents. The proposed cloud-assisted service includes a predictive model based on logistic regression to predict the occurrence of unforeseen incidents. The sudden slowdown of vehicles speeds is the practical case of the article. The classification task of the predictive model incorporates four explained variables, including vehicle speed, the travel time and estimated delay time. The prediction accuracy is proved by checking the model relevance according to the quality of fit and the statistical significance of each explained variable.

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 Development of a Decision Making Algorithm for Traffic Jams Reduction Applied to Intelligent Transportation Systems

2016 ◽  
Vol 2016 ◽  
pp. 1-16
Author(s):  
David Gómez ◽  
José-Fernán Martínez ◽  
Juana Sendra ◽  
Gregorio Rubio
Keyword(s):  
Decision Making ◽  
Intelligent Transportation Systems ◽  
Traffic Management ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Analytic Hierarchy ◽  
Traffic Jams ◽  
Traffic Management System ◽  
Smart Traffic ◽  
Hierarchy Process

This paper is aimed at developing a decision making algorithm for traffic jams reduction that can be applied to Intelligent Transportation Systems. To do so, these algorithms must address two main challenges that arise in this context. On one hand, there are uncertainties in the data received from sensor networks produced by incomplete information or because the information loses some of the precision during information processing and display. On the other hand, there is the variability of the context in which these types of systems are operating. More specifically, Analytic Hierarchy Process (AHP) algorithm has been adapted to ITS, taking into account the mentioned challenges. After explaining the proposed decision making method, it is validated in a specific scenario: a smart traffic management system.

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.

Ensuring the implementation of the modernized structure and automation of air traffic control processes in the area of responsibility of the Moscow district of air traffic control

2018 ◽  
pp. 46-54
Author(s):  
A. V. Strukova
Keyword(s):  
Traffic Control ◽  
Traffic Management ◽  
Air Traffic Control ◽  
Management System ◽  
Air Traffic Management ◽  
Air Traffic ◽  
Security System ◽  
System Description ◽  
Functional Capabilities ◽  
Traffic Management System

The article considers the new automated air traffic management system «Synthesis AR4», as well as a system description for ensuring the implementation of a modernized airspace structure, navigation and surveillance that provides technical capabilities. A number of functional capabilities and advantages of the airspace security system are presented.

scholarly journals Privacy-Preserving Smart Road-Pricing System with Trustworthiness Evaluation in VANETs

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3658
Author(s):  
Qingfeng Zhu ◽  
Sai Ji ◽  
Jian Shen ◽  
Yongjun Ren
Keyword(s):  
Traffic Control ◽  
Traffic Management ◽  
Location Privacy ◽  
Vehicular Ad Hoc Networks ◽  
Intelligent Transportation System ◽  
Smart Cities ◽  
Security Analysis ◽  
Geographical Location ◽  
Experimental Simulation ◽  
Control Center

With the advanced development of the intelligent transportation system, vehicular ad hoc networks have been observed as an excellent technology for the development of intelligent traffic management in smart cities. Recently, researchers and industries have paid great attention to the smart road-tolling system. However, it is still a challenging task to ensure geographical location privacy of vehicles and prevent improper behavior of drivers at the same time. In this paper, a reliable road-tolling system with trustworthiness evaluation is proposed, which guarantees that vehicle location privacy is secure and prevents malicious vehicles from tolling violations at the same time. Vehicle route privacy information is encrypted and uploaded to nearby roadside units, which then forward it to the traffic control center for tolling. The traffic control center can compare data collected by roadside units and video surveillance cameras to analyze whether malicious vehicles have behaved incorrectly. Moreover, a trustworthiness evaluation is applied to comprehensively evaluate the multiple attributes of the vehicle to prevent improper behavior. Finally, security analysis and experimental simulation results show that the proposed scheme has better robustness compared with existing approaches.

Traffic Monitoring and Congestion Management in the SCOOT Urban Traffic Control System

1998 ◽  
Vol 1634 (1) ◽  
pp. 118-122 ◽  
Author(s):  
David Bretherton ◽  
Keith Wood ◽  
Neil Raha
Keyword(s):  
Control System ◽  
Traffic Control ◽  
Detection System ◽  
Congestion Management ◽  
Traffic Monitoring ◽  
Urban Traffic ◽  
Incident Detection ◽  
The European Union ◽  
Traffic Control System ◽  
Urban Traffic Control

The SCOOT Urban Traffic Control system is now operating in over 170 cities worldwide, including 7 systems in North America. Since the first system was installed, there has been a continuous program of research and development to provide new facilities to meet the requirement of the traffic manager. The latest version of SCOOT (Version 3.1) incorporates a traffic information database, ASTRID, and an incident-detection system, INGRID, and provides a number of facilities for congestion control. The traffic monitoring facilities of SCOOT, including a new facility to estimate emissions from vehicles, and the current program of work to enhance the incident-detection system and to provide additional facilities to manage incidents and congestion are reported in this paper. The work is being carried out as part of the European Union, DGXIII 4th Framework project, COSMOS, with additional funding from the UK Department of Transport. The enhanced system is to be installed in the Kingston Borough of London, where it will be tested in combination with congestion warning information provided by variable message signs.

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