A V2I-based real-time traffic density estimation system in urban scenarios
The number of vehicles in our roads is drastically increasing, especially in developing countries. In addition, these vehicles tend to be concentrated in urban areas which present a large population. Since traffic jams have important and mostly negative consequences, such as increasing travel time,...
| Autores: | , , , , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2015 |
| País: | España |
| Institución: | Universitat Politècnica de València (UPV) |
| Repositorio: | RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia |
| Idioma: | inglés |
| OAI Identifier: | oai:riunet.upv.es:10251/64102 |
| Acceso en línea: | https://riunet.upv.es/handle/10251/64102 |
| Access Level: | acceso abierto |
| Palabra clave: | Vehicular networks Vehicular density estimation V2I communications Road side unit VANETs ARQUITECTURA Y TECNOLOGIA DE COMPUTADORES |
| Sumario: | The number of vehicles in our roads is drastically increasing, especially in developing countries. In addition, these vehicles tend to be concentrated in urban areas which present a large population. Since traffic jams have important and mostly negative consequences, such as increasing travel time, fuel consumption, and air pollution, governments are making efforts to alleviate the increasing traffic pressure, being vehicular density one of the main metrics used for assessing the road traffic conditions. However, vehicle density is highly variable in time and space, making it difficult to be estimated accurately. In this paper, we present a solution to estimate the density of vehicles in urban scenarios. Our proposal, that has been specially designed for vehicular networks, allows intelligent transportation systems to continuously estimate vehicular density by accounting for the number of beacons received per road side unit (RSU), and also considering the roadmap topology where the RSUs are located. Using V2I communications, we are able to estimate the traffic density in a certain area, which represents a key parameter to perform efficient traffic redirection, thereby reducing the vehicles’ travel time and avoiding traffic. |
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