A new context-aware approach to traffic congestion estimation

Vehicular traffic estimation is one of the major issues in intelligent transportation systems. Traffic information can be used by navigation systems to improve travel efficiency. Current traffic estimation systems rely on infrastructure deployment to monitor traffic state. Therefore, they are costly to implement. In this paper, we propose a new context-aware approach to traffic congestion estimation. The proposed system estimates traffic state based on fuzzy logic without need of any communication infrastructure. The fuzzy system uses vehicular contextual information including speed and acceleration of vehicle to estimate the local traffic congestion level. The proposed system is evaluated using three simulation scenarios with different traffic congestions. Simulation results indicate that the proposed system provides an accurate and efficient estimation of road traffic state, which can be exploited by traffic-aware applications.

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