Avaliação da qualidade da estimação de atributos de fluxo veicular a partir do processamento de imagens

Detalhes bibliográficos
Ano de defesa: 2018
Autor(a) principal: Lira, Johny Alves
Orientador(a): Cunto, Flávio José Craveiro
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Não Informado pela instituição
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Link de acesso: http://www.repositorio.ufc.br/handle/riufc/36459
Resumo: The increasing increase of the vehicular fleet and of the congestion of vehicles and traffic accidents generates need of better mechanisms of traffic management. The possibility of analyzing the trajectory of large-scale vehicles with greater autonomy is very useful for traffic management, and can subsidize decisions that involve the cost generated by the loss of time of users or money spent with accident victims. The method of extraction of vehicular trajectories may contain errors resulting from the adjustment of parameters of the extraction algorithm or the models used in it. The evaluation of its quality is important in that the traffic indicators are generated from the data exported by the algorithm. The estimation of the precision of the indicators calculated from the exported trajectories allows to inform the reliability that can be had in the estimates of the indicators. This work aims to evaluate the quality of vehicle trajectory extraction through image processing. For this, a vehicle tracking algorithm was consolidated and adjusted based on VISSIM microsimulator footage, in order to evaluate the quality of the tracing through error indicators exported by these. Twelve scenarios were generated for different camera heights, traffic operation regime and vehicular flow. Position and time information of each vehicle were obtained from the results of the algorithm and microsimulation in the VISSIM by which, visually, they presented a good overlap. The clustering model for feature based using a storage system proved to be efficient in dealing with interrupted flow regime. The results of this research presented a mean of the differences between -0.70 m and 0.67 m for the coordinate estimates, between -0.85 m and 0.11 m for the vehicular length, between -3.4% and 5.44% for the vehicle counts and below 0.95km / h and 1.10km / h for medium and instantaneous speeds, respectively. It was observed that the average velocities of the current estimated by the algorithm and by VISSIM were very close, that the standard of the average speed errors decreased with the increase of the height of the camera and that the use of VISSIM allowed a good evaluation of the quality of the tracking. Excluding external interferences, such as variation of luminosity, camera balance, obstacles and climate change, it was possible to evaluate traffic indicator errors alone, informing us of the origin and size of the errors.
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spelling Lira, Johny AlvesCunto, Flávio José Craveiro2018-10-11T16:50:03Z2018-10-11T16:50:03Z2018LIRA, Johny Alves. Avaliação da qualidade da estimação de atributos de fluxo veicular a partir do processamento de imagens. 2018. 96 f. Dissertação (Mestrado em Engenharia de Transportes)-Centro de Tecnologia, Universidade Federal do Ceará, Fortaleza, 2018.http://www.repositorio.ufc.br/handle/riufc/36459The increasing increase of the vehicular fleet and of the congestion of vehicles and traffic accidents generates need of better mechanisms of traffic management. The possibility of analyzing the trajectory of large-scale vehicles with greater autonomy is very useful for traffic management, and can subsidize decisions that involve the cost generated by the loss of time of users or money spent with accident victims. The method of extraction of vehicular trajectories may contain errors resulting from the adjustment of parameters of the extraction algorithm or the models used in it. The evaluation of its quality is important in that the traffic indicators are generated from the data exported by the algorithm. The estimation of the precision of the indicators calculated from the exported trajectories allows to inform the reliability that can be had in the estimates of the indicators. This work aims to evaluate the quality of vehicle trajectory extraction through image processing. For this, a vehicle tracking algorithm was consolidated and adjusted based on VISSIM microsimulator footage, in order to evaluate the quality of the tracing through error indicators exported by these. Twelve scenarios were generated for different camera heights, traffic operation regime and vehicular flow. Position and time information of each vehicle were obtained from the results of the algorithm and microsimulation in the VISSIM by which, visually, they presented a good overlap. The clustering model for feature based using a storage system proved to be efficient in dealing with interrupted flow regime. The results of this research presented a mean of the differences between -0.70 m and 0.67 m for the coordinate estimates, between -0.85 m and 0.11 m for the vehicular length, between -3.4% and 5.44% for the vehicle counts and below 0.95km / h and 1.10km / h for medium and instantaneous speeds, respectively. It was observed that the average velocities of the current estimated by the algorithm and by VISSIM were very close, that the standard of the average speed errors decreased with the increase of the height of the camera and that the use of VISSIM allowed a good evaluation of the quality of the tracking. Excluding external interferences, such as variation of luminosity, camera balance, obstacles and climate change, it was possible to evaluate traffic indicator errors alone, informing us of the origin and size of the errors.O crescente aumento da frota veicular e dos congestionamentos de veículos e acidentes de trânsito gera necessidade de melhores mecanismos de gerenciamento de tráfego. A possibilidade de análise da trajetória dos veículos em larga escala com maior autonomia é bastante útil para a gestão do tráfego, podendo subsidiar decisões que envolvem o custo gerado pela perda de tempo dos usuários ou pelo dinheiro gasto com vítimas de acidentes. O método da extração de trajetórias veiculares pode conter erros provenientes do ajuste de parâmetros do algoritmo de extração ou dos modelos nele empregados. A avaliação de sua qualidade é importante na medida em que os indicadores de tráfego são gerados a partir dos dados exportados pelo algoritmo. A estimativa de precisão dos indicadores calculados a partir das trajetórias exportadas permite informar a confiabilidade em que se pode ter nas estimativas dos indicadores. Este trabalho objetiva avaliar a qualidade da extração de trajetórias veiculares através do processamento de imagens. Para isso, um algoritmo de rastreamento veicular foi consolidado e ajustado com base em filmagens do microssimulador VISSIM, de modo a avaliar a qualidade do rastreamento através de indicadores de erros exportados por estes. Foram gerados doze cenários para diferentes alturas da câmera, regime de operação de tráfego e fluxo veicular. Foram obtidas informações de posição e tempo de cada veículo a partir dos resultados do algoritmo e da microssimulação no VISSIM pelos quais, visualmente, apresentaram uma boa sobreposição. O modelo de agrupamento para feature based que utiliza um sistema de memorização se mostrou eficiente para lidar com regime de fluxo interrompido. Os resultados desta pesquisa apresentaram médias das diferenças entre -0,70m e 0,67m para as estimativas de coordenada, entre -0,85m e 0,11m para o comprimento veicular, entre -3,4% e 5,44% para as de contagem veiculares e abaixo de 0,95km/h e 1,10km/h para velocidades média e instantânea, respectivamente. Foi observado que as velocidades médias da corrente estimada pelo algoritmo e pelo VISSIM foram muito próximas, que o padrão dos erros médios de velocidade diminuiu com o aumento da altura da câmera e que a utilização do VISSIM permitiu uma boa avaliação da qualidade do rastreamento. Excluindo-se as interferências externas, como variação de luminosidade, balanço de câmera, obstáculos e mudança de clima, foi possível avaliar os erros de indicadores de tráfego isoladamente, nos informando a origem e o tamanho dos erros.TransportesTrajetórias - VeículosProcessamento de imagensQuality of trackingVehicular trajectoriesImages processingAvaliação da qualidade da estimação de atributos de fluxo veicular a partir do processamento de imagensinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisporreponame:Repositório Institucional da Universidade Federal do Ceará (UFC)instname:Universidade Federal do Ceará (UFC)instacron:UFCinfo:eu-repo/semantics/openAccessORIGINAL2018_dis_jalira.pdf2018_dis_jalira.pdfapplication/pdf9265582http://repositorio.ufc.br/bitstream/riufc/36459/3/2018_dis_jalira.pdf3283a3ae11702cc1f091febbf3fb0447MD53LICENSElicense.txtlicense.txttext/plain; charset=utf-81788http://repositorio.ufc.br/bitstream/riufc/36459/4/license.txt89db4352906ed83f2ba5c6aed577d589MD54riufc/364592021-01-26 12:53:01.476oai:repositorio.ufc.br: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ório InstitucionalPUBhttp://www.repositorio.ufc.br/ri-oai/requestbu@ufc.br || repositorio@ufc.bropendoar:2021-01-26T15:53:01Repositório Institucional da Universidade Federal do Ceará (UFC) - Universidade Federal do Ceará (UFC)false
dc.title.pt_BR.fl_str_mv Avaliação da qualidade da estimação de atributos de fluxo veicular a partir do processamento de imagens
title Avaliação da qualidade da estimação de atributos de fluxo veicular a partir do processamento de imagens
spellingShingle Avaliação da qualidade da estimação de atributos de fluxo veicular a partir do processamento de imagens
Lira, Johny Alves
Transportes
Trajetórias - Veículos
Processamento de imagens
Quality of tracking
Vehicular trajectories
Images processing
title_short Avaliação da qualidade da estimação de atributos de fluxo veicular a partir do processamento de imagens
title_full Avaliação da qualidade da estimação de atributos de fluxo veicular a partir do processamento de imagens
title_fullStr Avaliação da qualidade da estimação de atributos de fluxo veicular a partir do processamento de imagens
title_full_unstemmed Avaliação da qualidade da estimação de atributos de fluxo veicular a partir do processamento de imagens
title_sort Avaliação da qualidade da estimação de atributos de fluxo veicular a partir do processamento de imagens
author Lira, Johny Alves
author_facet Lira, Johny Alves
author_role author
dc.contributor.author.fl_str_mv Lira, Johny Alves
dc.contributor.advisor1.fl_str_mv Cunto, Flávio José Craveiro
contributor_str_mv Cunto, Flávio José Craveiro
dc.subject.por.fl_str_mv Transportes
Trajetórias - Veículos
Processamento de imagens
Quality of tracking
Vehicular trajectories
Images processing
topic Transportes
Trajetórias - Veículos
Processamento de imagens
Quality of tracking
Vehicular trajectories
Images processing
description The increasing increase of the vehicular fleet and of the congestion of vehicles and traffic accidents generates need of better mechanisms of traffic management. The possibility of analyzing the trajectory of large-scale vehicles with greater autonomy is very useful for traffic management, and can subsidize decisions that involve the cost generated by the loss of time of users or money spent with accident victims. The method of extraction of vehicular trajectories may contain errors resulting from the adjustment of parameters of the extraction algorithm or the models used in it. The evaluation of its quality is important in that the traffic indicators are generated from the data exported by the algorithm. The estimation of the precision of the indicators calculated from the exported trajectories allows to inform the reliability that can be had in the estimates of the indicators. This work aims to evaluate the quality of vehicle trajectory extraction through image processing. For this, a vehicle tracking algorithm was consolidated and adjusted based on VISSIM microsimulator footage, in order to evaluate the quality of the tracing through error indicators exported by these. Twelve scenarios were generated for different camera heights, traffic operation regime and vehicular flow. Position and time information of each vehicle were obtained from the results of the algorithm and microsimulation in the VISSIM by which, visually, they presented a good overlap. The clustering model for feature based using a storage system proved to be efficient in dealing with interrupted flow regime. The results of this research presented a mean of the differences between -0.70 m and 0.67 m for the coordinate estimates, between -0.85 m and 0.11 m for the vehicular length, between -3.4% and 5.44% for the vehicle counts and below 0.95km / h and 1.10km / h for medium and instantaneous speeds, respectively. It was observed that the average velocities of the current estimated by the algorithm and by VISSIM were very close, that the standard of the average speed errors decreased with the increase of the height of the camera and that the use of VISSIM allowed a good evaluation of the quality of the tracking. Excluding external interferences, such as variation of luminosity, camera balance, obstacles and climate change, it was possible to evaluate traffic indicator errors alone, informing us of the origin and size of the errors.
publishDate 2018
dc.date.accessioned.fl_str_mv 2018-10-11T16:50:03Z
dc.date.available.fl_str_mv 2018-10-11T16:50:03Z
dc.date.issued.fl_str_mv 2018
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
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status_str publishedVersion
dc.identifier.citation.fl_str_mv LIRA, Johny Alves. Avaliação da qualidade da estimação de atributos de fluxo veicular a partir do processamento de imagens. 2018. 96 f. Dissertação (Mestrado em Engenharia de Transportes)-Centro de Tecnologia, Universidade Federal do Ceará, Fortaleza, 2018.
dc.identifier.uri.fl_str_mv http://www.repositorio.ufc.br/handle/riufc/36459
identifier_str_mv LIRA, Johny Alves. Avaliação da qualidade da estimação de atributos de fluxo veicular a partir do processamento de imagens. 2018. 96 f. Dissertação (Mestrado em Engenharia de Transportes)-Centro de Tecnologia, Universidade Federal do Ceará, Fortaleza, 2018.
url http://www.repositorio.ufc.br/handle/riufc/36459
dc.language.iso.fl_str_mv por
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instname_str Universidade Federal do Ceará (UFC)
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reponame_str Repositório Institucional da Universidade Federal do Ceará (UFC)
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