GPS trajectory clustering method for decision making on intelligent transportation systems

2020 ◽  
Vol 38 (5) ◽  
pp. 5529-5535
Author(s):  
Gary Reyes ◽  
Laura Lanzarini ◽  
Waldo Hasperué ◽  
Aurelio F. Bariviera
Keyword(s):  
Decision Making ◽  
Intelligent Transportation Systems ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Trajectory Clustering ◽  
Clustering Method ◽  
Gps Trajectory

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.

Multicriteria Project Portfolio Selection: Case Study for Intelligent Transportation Systems

2003 ◽  
Vol 1848 (1) ◽  
pp. 125-131 ◽  
Author(s):  
M. Reza Ghaeli ◽  
John Vavrik ◽  
Glenyth Nasvadi
Keyword(s):  
Decision Making ◽  
Portfolio Selection ◽  
Intelligent Transportation Systems ◽  
New Technologies ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Public Image ◽  
Project Portfolio ◽  
Project Portfolio Selection

Transportation strategies encompass a portfolio of projects in which choices must be made between competing alternatives. An appropriate portfolio of projects is essential for the success and growth of transportation agencies. The introduction and implementation of emerging technologies such as intelligent transportation systems (ITS) increase the need for more effective decision-making approaches and project selection in the coming years. Transportation projects, particularly, have a broad impact on the public and are multicriteria in nature. The projects also involve several elements of risk, such as project success, public acceptance, or public image. Traditional methods of project evaluation such as benefit–cost analysis focus mainly on the financial rewards of projects and do not sufficiently consider multicriteria and risk evaluations in an integrated framework. Development of an objective and systematic methodology that could address the multicriteria nature of the projects and also deal with their risks and rewards is necessary for both private and public agencies. This need is important particularly when new technologies are implemented, information on project impacts is insufficient, and resources are constrained. An integrated project portfolio selection model is introduced based on the well-established methodologies used for multicriteria evaluation and proven concepts used for portfolio selection in the finance discipline. The new methodology significantly facilitates decision making by integrating both the risk and the value of projects. A case study for selecting ITS projects in a public agency is demonstrated. Guidance is provided in nontechnical language for interpreting the outputs of the methodology.

Quality indicator of the smart city transportation and logistics system

2020 ◽  
Vol 19 (11) ◽  
pp. 2116-2135
Author(s):  
G.V. Savin
Keyword(s):  
Intelligent Transportation Systems ◽  
Smart City ◽  
Urban Areas ◽  
Human Life ◽  
Life Quality ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Logistics System ◽  
Organization And Management

Subject. The article considers functioning and development of process flows of transportation and logistics system of a smart city. Objectives. The study identifies factors and dependencies of the quality of human life on the organization and management of stream processes. Methods. I perform a comparative analysis of previous studies, taking into account the uniquely designed results, and the econometric analysis. Results. The study builds multiple regression models that are associated with stream processes, highlights interdependent indicators of temporary traffic and pollution that affect the indicator of life quality. However, the identified congestion indicator enables to predict the time spent in traffic jams per year for all participants of stream processes. Conclusions. The introduction of modern intelligent transportation systems as a component of the transportation and logistics system of a smart city does not fully solve the problems of congestion in cities at the current rate of urbanization and motorization. A viable solution is to develop cooperative and autonomous intelligent transportation systems based on the logistics approach. This will ensure control over congestion, the reduction of which will contribute to improving the life quality of people in urban areas.

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