Publication: Modos alternativos de transporte: Dynamic Ridesharing
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2014-09
Defense date
2014-09-25
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Abstract
El consumo energético, las congestiones de tráfico, las emisiones de contaminantes y los costes económicos son algunos de los factores negativos asociados al transporte privado. Para intentar reducir los efectos de estos se han planteado una serie de modos de transporte alternativos basados en el consumo eficiente de los recursos disponibles. Uno de estos modos o estrategias de transporte es el dynamic ridesharing. Este modelo trata de incrementar la tasa de ocupación media de los vehículos privados para, de forma colaborativa, disminuir el número de coches en circulación y por lo tanto los factores citados anteriormente. El ridesharing se basa en emparejar a una serie de usuarios con vehículo propio, dispuestos a desviarse de su ruta habitual a cambio de compartir los gastos del viaje, con otros usuarios con una necesidad de transporte. El dynamic ridesharing realiza estos emparejamientos en un periodo corto de tiempo, permitiendo a priori así su adopción masiva a través de dispositivos nómadas, como los smartphones.
El presente trabajo estudia este modelo de transporte, tanto desde el punto de vista cualitativo, realizando un estudio de la situación actual de este problema, como cuantitativo, desarrollando un modelo matemático del sistema y estudiando una serie de hipotéticos escenarios para comprobar la viabilidad de ridesharing. Para esto último es necesario emplear técnicas de programación lineal y optimización no lineal, cuya implementación y evaluación para este tipo de problemas será el objeto de la parte final de este trabajo.
Power consumption, traffic congestion, air pollution and economic costs are some of the negative factors associated with private transport. In order to reduce these effects, different transport modes have raised based on the efficient use of the available resources. One of these modes is the dynamic ridesharing. Dynamic ridesharing tries to increase the average occupation of private vehicles, in a collaborative way, in order to decrease the number of vehicles on road and to mitigate the previously described effects. The ridesharing problem is based on matching drivers, with their own vehicle, with riders and drivers requiring the minimal effort for both, and sharing the costs associated to the ride. Dynamic ridesharing arranges these matches on a very short notice. In this project we study the proposed transportation mode by analyzing the current state of the art of the problem and developing a mathematical model of the system. This model will be tested on artificial scenarios to prove its feasibility. To achieve such a task, the use of lineal programming and non-lineal optimization techniques will be necessary, being the implementation and evaluation of these algorithms to core work in this project final part.
Power consumption, traffic congestion, air pollution and economic costs are some of the negative factors associated with private transport. In order to reduce these effects, different transport modes have raised based on the efficient use of the available resources. One of these modes is the dynamic ridesharing. Dynamic ridesharing tries to increase the average occupation of private vehicles, in a collaborative way, in order to decrease the number of vehicles on road and to mitigate the previously described effects. The ridesharing problem is based on matching drivers, with their own vehicle, with riders and drivers requiring the minimal effort for both, and sharing the costs associated to the ride. Dynamic ridesharing arranges these matches on a very short notice. In this project we study the proposed transportation mode by analyzing the current state of the art of the problem and developing a mathematical model of the system. This model will be tested on artificial scenarios to prove its feasibility. To achieve such a task, the use of lineal programming and non-lineal optimization techniques will be necessary, being the implementation and evaluation of these algorithms to core work in this project final part.
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Keywords
Modelos de transporte, Optimización, Programación lineal, Algoritmos genéticos, Dynamic ridesharing, Transport network, Optimization, Linear programming, Genetic algorithms