Sistema centralizado para la optimización del tráfico mediante un servidor de rutas
[EN] The route planning solutions promise improvements in terms of the travel time for a route if they are familiar with the traffic congestion state in real-time. With current solutions, where most are static and based on, the cost of road segments, the first challenge is to obtain reliable estimat...
| Autor: | |
|---|---|
| Tipo de recurso: | tesis de maestría |
| Fecha de publicación: | 2015 |
| País: | España |
| Institución: | Universitat Politècnica de València (UPV) |
| Repositorio: | RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia |
| Idioma: | español |
| OAI Identifier: | oai:riunet.upv.es:10251/67300 |
| Acceso en línea: | https://riunet.upv.es/handle/10251/67300 |
| Access Level: | acceso abierto |
| Palabra clave: | Redes vehiculares Interfaz ABATIS OMNeT++ SUMO Vehicular network Interface ARQUITECTURA Y TECNOLOGIA DE COMPUTADORES Máster Universitario en Ingeniería de Computadores-Màster Universitari en Enginyeria de Computadors |
| Sumario: | [EN] The route planning solutions promise improvements in terms of the travel time for a route if they are familiar with the traffic congestion state in real-time. With current solutions, where most are static and based on, the cost of road segments, the first challenge is to obtain reliable estimates of traffic congestion for a city at different times of day, and for different days of the year. Overall, calculating this amount of data will take a long time, and have a high computational cost when evaluating the optimal routes based on dependencies. In this paper, the feasibility of integrating a route recommendation system, a network simulator and a traffic simulator is studied. In particular we study the integration of OMNeT ++ and SUMO, both widely known and used tools, with the ABATIS route server as a solution for route planning, allowing to investigate what are the different effects on vehicle flows densely populated urban areas. To achieve that goal the traffic patterns adopted are adjusted, following driver models ranging from real-time speed changes to changes in route selection. However, the number of vehicles that have to be introduced in the simulation is unknown, and thus we developed a heuristic to adjust the number of vehicles to be injected based on the number of vehicles detected on the different sensors placed along the main streets of Valencia, Spain. Initial results show that the proposed route server offers routes with similar quality compared to the tool integrated in SUMO, and that the use of alternative routes is likely to introduce significant changes on the travel times of vehicles |
|---|