Editorial: Models and Technologies for Intelligent Transportation Systems: New Challenges and Metaheuristic Solutions for Large-Scale Network Applications

2013 ◽  
Vol 18 (1) ◽  
pp. 1-4 ◽  
Author(s):  
Francesco Viti ◽  
Chris Tampère
Keyword(s):  
Intelligent Transportation Systems ◽  
Large Scale ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Network Applications ◽  
Large Scale Network ◽  
Scale Network ◽  
New Challenges

On Modeling and Verification of Agent-Based Traffic Simulation Properties in Alloy

2012 ◽  
Vol 4 (4) ◽  
pp. 38-60 ◽  
Author(s):  
Junia Valente ◽  
Frederico Araujo ◽  
Rym Z. Wenkstern
Keyword(s):  
Intelligent Transportation Systems ◽  
Large Scale ◽  
Traffic Simulation ◽  
Simulation Models ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Agent Based ◽  
Traffic Models ◽  
First Order ◽  
New Generation

The advances in Intelligent Transportation Systems (ITS) call for a new generation of traffic simulation models that support connectivity and collaboration among simulated vehicles and traffic infrastructure. In this paper we introduce MATISSE, a complex, large scale agent-based framework for the modeling and simulation of ITS and discuss how Alloy, a modeling language based on set theory and first order logic, was used to specify, verify, and analyze MATISSE’s traffic models.

scholarly journals Automatic Extraction of Structural and Non-Structural Road Edges from Mobile Laser Scanning Data

Sensors ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 5030 ◽  
Author(s):  
Yang ◽  
Liu ◽  
Jiang ◽  
Xu ◽  
Sheng ◽  
...  
Keyword(s):  
Intelligent Transportation Systems ◽  
Laser Scanning ◽  
Large Scale ◽  
Auxiliary Information ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Road Maintenance ◽  
The Road ◽  
Large Scale Data ◽  
Road Width

Accurate road information is important for applications involving road maintenance, intelligent transportation, and road network updates. Mobile laser scanning (MLS) can effectively extract road information. However, accurately extracting road edges based on large-scale data for complex road conditions, including both structural and non-structural road types, remains difficult. In this study, a robust method to automatically extract structural and non-structural road edges based on a topological network of laser points between adjacent scan lines and auxiliary surfaces is proposed. The extraction of road and curb points was achieved mainly from the roughness of the extracted surface, without considering traditional thresholds (e.g., height jump, slope, and density). Five large-scale road datasets, containing different types of road curbs and complex road scenes, were used to evaluate the practicality, stability, and validity of the proposed method via qualitative and quantitative analyses. Measured values of the correctness, completeness, and quality of extracted road edges were over 95.5%, 91.7%, and 90.9%, respectively. These results confirm that the proposed method can extract road edges from large-scale MLS datasets without the need for auxiliary information on intensity, image, or geographic data. The proposed method is effective regardless of whether the road width is fixed, the road is regular, and the existence of pedestrians and vehicles. Most importantly, the proposed method provides a valuable solution for road edge extraction that is useful for road authorities when developing intelligent transportation systems, such as those required by self-driving vehicles.

scholarly journals VNF Chain Placement for Large Scale IoT of Intelligent Transportation

Sensors ◽  
2020 ◽  
Vol 20 (14) ◽  
pp. 3819
Author(s):  
Xing Wu ◽  
Jing Duan ◽  
Mingyu Zhong ◽  
Peng Li ◽  
Jianjia Wang
Keyword(s):  
Network Topology ◽  
Traffic Safety ◽  
Large Scale ◽  
Intelligent Transportation ◽  
Full Potential ◽  
Service Chain ◽  
Network Function ◽  
Large Scale Network ◽  
Scale Network ◽  
Over Time

With the advent of the Internet of things (IoT), intelligent transportation has evolved over time to improve traffic safety and efficiency as well as to reduce congestion and environmental pollution. However, there are some challenging issues to be addressed so that it can be implemented to its full potential. The major challenge in intelligent transportation is that vehicles and pedestrians, as the main types of edge nodes in IoT infrastructure, are on the constant move. Hence, the topology of the large scale network is changing rapidly over time and the service chain may need reestablishment frequently. Existing Virtual Network Function (VNF) chain placement methods are mostly good at static network topology and any evolvement of the network requires global computation, which leads to the inefficiency in computing and the waste of resources. Mapping the network topology to a graph, we propose a novel VNF placement method called BVCP (Border VNF Chain Placement) to address this problem by elaborately dividing the graph into multiple subgraphs and fully exploiting border hypervisors. Experimental results show that BVCP outperforms the state-of-the-art method in VNF chain placement, which is highly efficient in large scale IoT of intelligent transportation.

Study on the Transmission Data Collection Technique of Network Applications

2012 ◽  
Vol 546-547 ◽  
pp. 1453-1458
Author(s):  
Hai Yan Liu ◽  
Zhao Hong Yang ◽  
Hong Liu Cai
Keyword(s):  
Data Collection ◽  
Large Scale ◽  
Original System ◽  
Application Layer ◽  
Analysis And Evaluation ◽  
Network Applications ◽  
Large Scale Network ◽  
Transmission Data ◽  
Scale Network ◽  
Data Collection Technique

In Large-scale network applications, transmission data collection is the basis for audit, analysis and evaluation of systems and users. Transmission data collection can be carried out either on the link line or on the host where the network application is running. Collecting at different locations, the types of data acquired are different, thus need different processing. This paper first analyzes the different transmission data collection methods, their advantages as well as disadvantages. Then analyzes the structure of those network applications that are basing on transmission dynamic linked library, promotes the intermediate DLL method. Finally through an example it shows how to define the intermediate DLL to collect transferred data on application layer without affecting the original system function.

scholarly journals Generic Framework for the Optimal Implementation of Flexibility Mechanisms in Large-Scale Smart Grids

2021 ◽  
Author(s):  
Alejandro J. del Real ◽  
Andrés Pastor ◽  
Jaime Durán
Keyword(s):  
Smart Grids ◽  
Large Scale ◽  
Mathematical Framework ◽  
Demand And Supply ◽  
Network Applications ◽  
Large Scale Network ◽  
Control Framework ◽  
Scale Network ◽  
The One ◽  
Optimal Implementation

This paper aims to provide the smart grid research community with an open and accessible general mathematical framework to develop and implement optimal flexibility mechanisms in large-scale network applications. The motivation of this paper is twofold. On the one hand, flexibility mechanisms are currently a hot topic of research, which is aimed to mitigate variation and uncertainty of electricity demand and supply in decentralised grids with a high aggregated share of renewables. On the other hand, a large part of such related research is performed by heuristic methods, which are generally inefficient (such methods do not guarantee optimality) and difficult to extrapolate for different use cases. Alternatively, this paper presents an MPC-based (Model Predictive Control) framework explicitly including a generic flexibility mechanism which is easy to particularise to specific strategies such as Demand Response, Flexible Production and Energy Efficiency Services. The proposed framework is benchmarked with other non-optimal control configurations to better show the advantages it provides. The work of this paper is completed by the implementation of a generic use case which aims to further clarify the use of the framework and thus, to ease its adoption by other researchers in their specific flexibility mechanisms applications.

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