scholarly journals Graph-based ahead monitoring of vulnerabilities in large dynamic transportation networks

PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0248764
Author(s):  
Angelo Furno ◽  
Nour-Eddin El Faouzi ◽  
Rajesh Sharma ◽  
Eugenio Zimeo
Keyword(s):  
Control Systems ◽  
Traffic Control ◽  
Large Scale ◽  
Transportation Networks ◽  
Smart Cities ◽  
Dynamic Networks ◽  
Computation Time ◽  
Weighted Graphs ◽  
Dynamic Graphs ◽  
Physical Infrastructure

Betweenness Centrality (BC) has proven to be a fundamental metric in many domains to identify the components (nodes) of a system modelled as a graph that are mostly traversed by information flows thus being critical to the proper functioning of the system itself. In the transportation domain, the metric has been mainly adopted to discover topological bottlenecks of the physical infrastructure composed of roads or railways. The adoption of this metric to study the evolution of transportation networks that take into account also the dynamic conditions of traffic is in its infancy mainly due to the high computation time needed to compute BC in large dynamic graphs. This paper explores the adoption of dynamic BC, i.e., BC computed on dynamic large-scale graphs, modeling road networks and the related vehicular traffic, and proposes the adoption of a fast algorithm for ahead monitoring of transportation networks by computing approximated BC values under time constraints. The experimental analysis proves that, with a bounded and tolerable approximation, the algorithm computes BC on very large dynamically weighted graphs in a significantly shorter time if compared with exact computation. Moreover, since the proposed algorithm can be tuned for an ideal trade-off between performance and accuracy, our solution paves the way to quasi real-time monitoring of highly dynamic networks providing anticipated information about possible congested or vulnerable areas. Such knowledge can be exploited by travel assistance services or intelligent traffic control systems to perform informed re-routing and therefore enhance network resilience in smart cities.

Cyber Space and Aviation 4.0 – New Testing Facilities for Next Generation of Cyber-Physical, Autonomous and Air Traffic Control Systems

2021 ◽  
Author(s):  
Miroslaw Nawrocki ◽  
Krzysztof Kurowski ◽  
Radoslaw Gorzenski
Keyword(s):  
Control Systems ◽  
Traffic Control ◽  
Large Scale ◽  
Gradual Transition ◽  
Information And Communications Technologies ◽  
Early Experiences ◽  
Emerging Trends ◽  
Service Oriented ◽  
Cyber Space ◽  
New Generation

Transforming basic multi-disciplinary research into applied research in the area of a new generation of networks, sensors, cyber-physical, and edge-cloud systems used for cyber space is a difficult task. However, moving even a step forward by providing advanced field and testing facilities for ground-air demonstrations for appearing Aviation 4.0 scenarios is a real challenge. In our opinion, such a rapid and dynamic process should be powered by many research and infrastructure projects. New development strategies are needed in the upcoming future to link emerging trends in information and communications technologies together with increased competitiveness and users expectations from fully autonomous drones, robots, cars, etc. This paper aims to share our early experiences in setting and providing distributed testbeds to cross different hardware, software, and cyber-physical components and pave the way for air-ground demonstrations of the new emerging IT paradigm – digital continuum. We also share our vision of implementing virtual and digital spaces at a large scale by the gradual transition towards higher levels of cyber-physical systems automation and autonomy. Finally, we promote dynamic, data-driven, service-oriented approaches and network-centric platforms for a new generation of air and ground control systems which will be validated in real conditions established thanks to our new airfield-based laboratories used in many ongoing and future R&D projects.

scholarly journals Adaptive Performance Optimization for Large-Scale Traffic Control Systems

2009 ◽  
Vol 42 (15) ◽  
pp. 76-83
Author(s):  
A. Kouvelas ◽  
E. Kosmatopoulos ◽  
M. Papageorgiou ◽  
K. Aboudolas
Keyword(s):  
Control Systems ◽  
Traffic Control ◽  
Performance Optimization ◽  
Large Scale ◽  
Adaptive Performance

scholarly journals Adaptive Performance Optimization for Large-Scale Traffic Control Systems

2011 ◽  
Vol 12 (4) ◽  
pp. 1434-1445 ◽  
Author(s):  
Anastasios Kouvelas ◽  
Konstantinos Aboudolas ◽  
Elias B. Kosmatopoulos ◽  
Markos Papageorgiou
Keyword(s):  
Control Systems ◽  
Traffic Control ◽  
Performance Optimization ◽  
Large Scale ◽  
Adaptive Performance

scholarly journals An Incentive Based Dynamic Ride-Sharing System for Smart Cities

Smart Cities ◽  
2021 ◽  
Vol 4 (2) ◽  
pp. 532-547
Author(s):  
Abu Saleh Md Bakibillah ◽  
Yi Feng Paw ◽  
Md Abdus Samad Kamal ◽  
Susilawati Susilawati ◽  
Chee Pin Tan
Keyword(s):  
Control Systems ◽  
Traffic Control ◽  
Smart Cities ◽  
Flow Behavior ◽  
Urban Mobility ◽  
Microscopic Traffic Simulation ◽  
The Road ◽  
Road Capacity ◽  
Ride Sharing ◽  
Traffic Performance

Connected and automated vehicle (CAV) technology, along with advanced traffic control systems, cannot ensure congestion-free traffic when the number of vehicles exceeds the road capacity. To address this problem, in this paper, we propose a dynamic ride-sharing system based on incentives (for both passengers and drivers) that incorporates travelers of similar routes and time schedules on short notice. The objective is to reduce the number of private vehicles on urban roads by utilizing the available seats properly. We develop a mobile-cloud architecture-based system that enables real-time ride-sharing. The effectiveness of the proposed system is evaluated through microscopic traffic simulation using Simulation of Urban Mobility (SUMO) considering the traffic flow behavior of a real smart city. Moreover, we develop a lab-scale experimental prototype in the form of Internet of Things (IoT) network. The simulation results show that the proposed system reduces fuel consumption, CO2 and CO emissions, and average waiting time of vehicles significantly, while increasing the vehicle’s average speed. Remarkably, it is found that only 2–10% ride-sharing can improve the overall traffic performance.

scholarly journals RITM3 as the Digital Platform for Traffic Management in Smart Cities

2020 ◽  
Vol 157 ◽  
pp. 05004
Author(s):  
Andrey Burmistrov ◽  
Maria Siniavina ◽  
Olga Rasskazova ◽  
Igor Alexandrov
Keyword(s):  
Control Systems ◽  
Real Time ◽  
Traffic Control ◽  
Traffic Management ◽  
Smart Cities ◽  
Time Integration ◽  
Urban Transport ◽  
Digital Platform ◽  
Adaptive Traffic Control ◽  
Transport Management

The paper reviews major problems of cities related to the management of transport flows; it looks at fundamental Russian legislative acts regulating the improvement of the urban transport management systems; briefly reviews information about the Adaptive Traffic Control Systems which are extensively used across the world cities and reflects on the capabilities of the Russian digital platform RITM3 (Real time Integration Transport Measurements Modeling Management), which is the evolution of the TransInfo software developed by the St. Petersburg company SIMETRA (formerly “A+S Transproject”). Digital platform RITM3 is designed for modeling traffic flows in cities and proactive traffic management in real time. The article also provides information about the experience of digital platform RITM3 application in Moscow.

scholarly journals DYNAMIC FAULT ANALYSIS OF LARGE-SCALE TRAFFIC CONTROL SYSTEMS WITH REFERENCE TO COMPONENT'S DETERIORATION

2008 ◽  
Vol 64 (3) ◽  
pp. 295-310
Author(s):  
Kouji YAMAMOTO ◽  
Kazuya AOKI ◽  
Kiyoyuki KAITO ◽  
Kiyoshi KOBAYASHI
Keyword(s):  
Control Systems ◽  
Traffic Control ◽  
Large Scale ◽  
Fault Analysis
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