Cooperative in-vehicle sensing of adverse road-weather conditions

Detalhes bibliográficos
Autor(a) principal: Correia, Ricardo Alexandre Leite
Data de Publicação: 2021
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10773/31605
Resumo: Given the increasing use of vehicles and the need to protect passengers, road safety has been of great importance in recent times. One of the main causes of road accidents is directly related to weather conditions, namely rain and wet conditions, which respectively decrease the visibility and stability of the car. Currently, weather stations are used to determine only the weather conditions. However, intelligent transportation systems are becoming more complex and adopting new models to interpret the conditions of the environment and disseminate the information more quickly and efficiently. Cooperative Intelligent Transport Systems are meant to achieve this purpose based on cooperative sensors and the Internet of Things (IoT), while ensuring greater coordination, either by the information made available to the driver, from communication systems such as Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I), or by using the vehicle sensors as a reference for traffic conditions. An interactive algorithm was developed, alongside the driver, to identify the necessary parameters to study the weather conditions. This algorithm is divided into several processes, that are specified within the intra-vehicular communication through proprietary signals, such as the state of the windshield wiper to detect rain, headlight position as a way to assess visibility and wheel speed to analyze the state of the surface and possible accident causes. The algorithm is composed by several methods, due to the different representations presented by the parameters. Thourght implementing different processes of detection parameters represented by only one bit of information and for parameters that have one or more bytes of information. Through using reverse engineering, the purpose is not only to interpret the transitions that occur in the signals and, after a filtering process, detect the position and the message identifier of the desired parameter, but also to correlate and compare these signals with the OBD-II (On-Board Diagnostic) diagnostic responses without a large set of data and in a short period of time. Afterwards, the parameters are transmitted to an On-Board Unit (OBU) platform that broadcasts the data using cooperative messages to the vehicle’s network. Tests were performed in two cars and the results obtained were satisfactory. All binary parameters were found in the first car, but not in the non-binary parameters, whereas on the second car is founded. However, these events allowed to acquire knowledge about the matter in which car manufacturers develop their intra-vehicular systems. It can, therefore, be concluded that this work adds an important step in this field.
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spelling Cooperative in-vehicle sensing of adverse road-weather conditionsIn-vehicle networksWeather conditionsRoad conditionsVehicular communicationsIntelligent transport systemsRoad safetyGiven the increasing use of vehicles and the need to protect passengers, road safety has been of great importance in recent times. One of the main causes of road accidents is directly related to weather conditions, namely rain and wet conditions, which respectively decrease the visibility and stability of the car. Currently, weather stations are used to determine only the weather conditions. However, intelligent transportation systems are becoming more complex and adopting new models to interpret the conditions of the environment and disseminate the information more quickly and efficiently. Cooperative Intelligent Transport Systems are meant to achieve this purpose based on cooperative sensors and the Internet of Things (IoT), while ensuring greater coordination, either by the information made available to the driver, from communication systems such as Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I), or by using the vehicle sensors as a reference for traffic conditions. An interactive algorithm was developed, alongside the driver, to identify the necessary parameters to study the weather conditions. This algorithm is divided into several processes, that are specified within the intra-vehicular communication through proprietary signals, such as the state of the windshield wiper to detect rain, headlight position as a way to assess visibility and wheel speed to analyze the state of the surface and possible accident causes. The algorithm is composed by several methods, due to the different representations presented by the parameters. Thourght implementing different processes of detection parameters represented by only one bit of information and for parameters that have one or more bytes of information. Through using reverse engineering, the purpose is not only to interpret the transitions that occur in the signals and, after a filtering process, detect the position and the message identifier of the desired parameter, but also to correlate and compare these signals with the OBD-II (On-Board Diagnostic) diagnostic responses without a large set of data and in a short period of time. Afterwards, the parameters are transmitted to an On-Board Unit (OBU) platform that broadcasts the data using cooperative messages to the vehicle’s network. Tests were performed in two cars and the results obtained were satisfactory. All binary parameters were found in the first car, but not in the non-binary parameters, whereas on the second car is founded. However, these events allowed to acquire knowledge about the matter in which car manufacturers develop their intra-vehicular systems. It can, therefore, be concluded that this work adds an important step in this field.A segurança rodoviária apresenta uma grande relevância durante os últimos tempos, dado o aumento da utilização de veículos e a necessidade de proteger os passageiros. Umas das principais causas dos acidentes rodoviários está diretamente relacionada com as condições meteorológicas, nomeadamente a chuva e o piso molhado, que diminuem a visibilidade e a estabilidade do carro, respectivamente. Atualmente, apenas são usadas estações meteorológicas para determinar as condições do tempo, porém, os sistemas inteligentes de transportes estão a tornar-se mais complexos e a adotar novos modelos para interpretar as condições do meio e difundir a informação de forma mais rápida e eficiente. Ao nível dos sistemas de transportes inteligentes cooperativos (C-ITS), pretende-se atingir esse propósito com base em sensorização cooperativa e Internet das Coisas (IoT), garantindo uma maior coordenação, quer pela informação disponibilizada ao condutor, a partir de sistemas de comunicação como V2V (veiculo-para-veiculo) e V2I (veiculopara- infraestrutura), quer pela utilização dos próprios sensores dos veículos como referência das condições de circulação. Neste trabalho desenvolveu-se um algoritmo interativo com o condutor para identificar os parâmetros necessários para o estudo das condições meteorológicas, através dos sinais proprietários que se encontram especificados na comunicação intra-veicular, como por exemplo o estado do limpa pára-brisas para identificar situações de aguaceiros ou chuva intensa, a posição das luzes como forma de avaliar a visibilidade da estrada e a velocidade das rodas para analisar o estado do piso e possíveis causas de acidentes. Devido às diferentes representações que os parâmetros apresentam, o algoritmo é constituído por vários métodos, implementando diferentes processos para a detecção de parâmetros em que só apresentam um bit de informação e para parâmetros que dispõem de um ou mais bytes de informação. Com o recurso métodos de engenharia reversa, o objetivo passa, não só, por interpretar as transições que vão acontecendo nos sinais e, após um processo de filtragem, detetar a posição e o identificador da mensagem onde se encontra o parâmetro pretendido, mas também, por correlacionar e comparar esses sinais com as respostas de diagnóstico OBD-II (On-Board Diagnostics) sem ser necessário aceder a um vasto conjunto de dados, num curto espaço de tempo. Posteriormente, os parâmetros são transmitidos para uma plataforma OBU que difunde os dados através de mensagens cooperativas para a rede veicular. Foram realizados testes em dois carros, sendo os resultados obtidos satisfatórios. No primeiro carro foram encontrados todos os parâmetros binários, mas não se obteve o mesmo resultado nos parâmetros não-binários, contrariamente ao segundo carro. Contudo, estes acontecimentos permitiram adquirir conhecimento sobre a forma como os fabricantes de automóveis desenvolvem os seus sistemas intra-veiculares. Conclui-se assim que este trabalho acrescenta um passo importante nesta área.2021-07-21T10:01:11Z2021-02-26T00:00:00Z2021-02-26info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10773/31605engCorreia, Ricardo Alexandre Leiteinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-02-22T12:01:01Zoai:ria.ua.pt:10773/31605Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:03:26.893812Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Cooperative in-vehicle sensing of adverse road-weather conditions
title Cooperative in-vehicle sensing of adverse road-weather conditions
spellingShingle Cooperative in-vehicle sensing of adverse road-weather conditions
Correia, Ricardo Alexandre Leite
In-vehicle networks
Weather conditions
Road conditions
Vehicular communications
Intelligent transport systems
Road safety
title_short Cooperative in-vehicle sensing of adverse road-weather conditions
title_full Cooperative in-vehicle sensing of adverse road-weather conditions
title_fullStr Cooperative in-vehicle sensing of adverse road-weather conditions
title_full_unstemmed Cooperative in-vehicle sensing of adverse road-weather conditions
title_sort Cooperative in-vehicle sensing of adverse road-weather conditions
author Correia, Ricardo Alexandre Leite
author_facet Correia, Ricardo Alexandre Leite
author_role author
dc.contributor.author.fl_str_mv Correia, Ricardo Alexandre Leite
dc.subject.por.fl_str_mv In-vehicle networks
Weather conditions
Road conditions
Vehicular communications
Intelligent transport systems
Road safety
topic In-vehicle networks
Weather conditions
Road conditions
Vehicular communications
Intelligent transport systems
Road safety
description Given the increasing use of vehicles and the need to protect passengers, road safety has been of great importance in recent times. One of the main causes of road accidents is directly related to weather conditions, namely rain and wet conditions, which respectively decrease the visibility and stability of the car. Currently, weather stations are used to determine only the weather conditions. However, intelligent transportation systems are becoming more complex and adopting new models to interpret the conditions of the environment and disseminate the information more quickly and efficiently. Cooperative Intelligent Transport Systems are meant to achieve this purpose based on cooperative sensors and the Internet of Things (IoT), while ensuring greater coordination, either by the information made available to the driver, from communication systems such as Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I), or by using the vehicle sensors as a reference for traffic conditions. An interactive algorithm was developed, alongside the driver, to identify the necessary parameters to study the weather conditions. This algorithm is divided into several processes, that are specified within the intra-vehicular communication through proprietary signals, such as the state of the windshield wiper to detect rain, headlight position as a way to assess visibility and wheel speed to analyze the state of the surface and possible accident causes. The algorithm is composed by several methods, due to the different representations presented by the parameters. Thourght implementing different processes of detection parameters represented by only one bit of information and for parameters that have one or more bytes of information. Through using reverse engineering, the purpose is not only to interpret the transitions that occur in the signals and, after a filtering process, detect the position and the message identifier of the desired parameter, but also to correlate and compare these signals with the OBD-II (On-Board Diagnostic) diagnostic responses without a large set of data and in a short period of time. Afterwards, the parameters are transmitted to an On-Board Unit (OBU) platform that broadcasts the data using cooperative messages to the vehicle’s network. Tests were performed in two cars and the results obtained were satisfactory. All binary parameters were found in the first car, but not in the non-binary parameters, whereas on the second car is founded. However, these events allowed to acquire knowledge about the matter in which car manufacturers develop their intra-vehicular systems. It can, therefore, be concluded that this work adds an important step in this field.
publishDate 2021
dc.date.none.fl_str_mv 2021-07-21T10:01:11Z
2021-02-26T00:00:00Z
2021-02-26
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