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Master's Dissertation
DOI
10.11606/D.3.2013.tde-19092014-115054
Document
Author
Full name
Eduardo Jun Shinohara
E-mail
Institute/School/College
Knowledge Area
Date of Defense
Published
São Paulo, 2013
Supervisor
Committee
Quintanilha, José Alberto (President)
Giannotti, Mariana Abrantes
Hamburger, Diana Sarita
Title in Portuguese
Modelagem do comportamento espaço-temporal de veículo rastreado.
Keywords in Portuguese
Sistemas de informações geográficas
Sistemas inteligentes de transportes
Veículos (Monitoramento)
Abstract in Portuguese
No Brasil existe a perspectiva de crescimento expressivo do volume de dados a ser processado pelas prestadoras de serviços de rastreamento em decorrência do aumento natural do uso de sistemas de rastreamento e também para atender a Resolução 330 de 2009 e Deliberação 135 de 30/01/2013 do Conselho Nacional de Trânsito (CONTRAN). Este crescimento gera a necessidade da incorporação de ferramentas analíticas nos sistemas de gerenciamento do rastreamento e monitoramento de veículos e na gestão de risco, para aumentar a sua eficiência e atender o crescimento do mercado. O objetivo desta dissertação é de propor uma metodologia que permita caracterizar o comportamento de movimentação de um veículo, com a finalidade de auxiliar o processo de tomada de decisão no gerenciamento e monitoramento de veículos. A caracterização do comportamento de movimentação do veículo foi feita pela geração de um modelo analítico do comportamento de movimentação, coletando os dados pretéritos da posição espacial e temporal. Este modelo baseia-se na movimentação e considera os aspectos comportamentais espaciais e temporais de forma independente. A caracterização do comportamento gera informações para identificar o comportamento espacial e temporal do veículo monitorado para um determinado nível de confiabilidade.
Title in English
Modelling the space-temporal behavior of tracked vehicle.
Keywords in English
Automatic Vehicle Location (AVL)
Information System (GIS)
Intelligent Transportation System (ITS)
Spatial analysis
Vehicle monitoring
Abstract in English
In Brazil there is the prospect of growth in the volume of data to be processed by the tracking service providers due to the natural increase of the use of tracking systems and also to meet the Resolution 330 of 2009 and Resolution 135 of 01.30.2013 of the National Traffic Council (CONTRAN), due to this growth the need of incorporation of analytical tools in systems management tracking and monitoring of vehicles and risk management are created, to increase their efficiency and meet market growth. This study objective is to propose a methodology to characterize the moving vehicle behavior, in order to assist the process of decision making in management and vehicle tagging. The vehicle handling behavior will be characterized by generating an analytical model of the vehicle movement, collecting bygone data of spatial position and time. This model will consist of a motion model taking into account that the spatial and temporal aspects of behavior are taken independently. The behavior characterization generates reports able to identify the spatial and temporal behavior of the monitored vehicle for a given level of reliability.
 
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Publishing Date
2014-09-22
 
WARNING: The material described below relates to works resulting from this thesis or dissertation. The contents of these works are the author's responsibility.
  • MANFRE, L. A., et al. An Analysis of Geospatial Technologies for Risk and Natural Disaster Management [doi:10.3390/ijgi1020166]. ISPRS International Journal of Geo-Information [online], 2012, vol. 1, p. 166-185.
  • BARROS, D., et al. Characterizing urban land use pattern by variograms parameters from multispectral high spatial resolution satllite images: an application in Salvador, Bahia - Brazil. In IGARSS 2013 - Int. Geoscience and Remote Sensing Symposium, Melbourne - Australia, 2013. Proceedings of., 2013.
  • MANFRE, L. A., et al. Assessment of SVM classification process for landslides identification. In 10th International Symposium of Spatial Accuracy Assessment in Natural Resource and Environmental Sciences - Accuracy 2012, Florianópolis - Sta Catarina, 2012. Proceedings of 10th International Symposium of Spatial Accuracy Assessment in Natural Resource and Environmental Sciences - Accuracy 2012., 2012.
  • SARTOR, S. M., et al. Tools for Coastal Marine Ecosystem-Based Management and Geographically Referred Data Integration - the Santos Region case study. In GSDI 11 World Conference - Spatial Data Infrastructure Convergence: Building SDI Bridges to Address Global Challenges., Rotterdam, 2009. GSDI 11 World Conference., 2009.
  • SHINOHARA, E. J., et al. Uso da ferramenta de análise geoestatística para estudo de atrito em pista de aeroporto. In XX ANPET - Congresso de Pesquisa e Ensino em Transportes, Brasília, 2006. Anais do XX ANPET - Congresso de Pesquisa e Ensino em Transportes. : ANPET, 2006.
All rights of the thesis/dissertation are from the authors
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