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Driver State Monitoring Systems (DSMS) play a crucial role in determining whether the driver is prepared to take control of the vehicle or not. In this paper we present a cost-efficient, context-aware system, based on smartphones, which supports the driver in the driving task. This is through monitoring the driver attention and drowsiness, in addition to detecting pedestrians and vehicles. The detection...
Driverless vehicles have received a great deal of attention in the Intelligent Transportation Systems (ITS) research fields during the last decade. Moreover, with the release of several intelligent vehicles to the roads, the necessity of cooperation and coordination among the vehicles, infrastructure and road users is increasing. In order to implement these approaches, a proper communication architecture...
The use of smartphones in a road context by drivers and Vulnerable Road Users (VRU) is rapidly increasing. To reduce the risks related to the influence of smartphone usage in a situation where traffic needs to be considered, a collision prediction algorithm is proposed based on Pedestrian to Vehicle (P2V) and Vehicle to Pedestrian (V2P) communication technologies, which increases the visual situational...
Road safety applications require the most reliable data. In recent years data fusion is becoming one of the main technologies for Advance Driver Assistant Systems (ADAS) to overcome the limitations of isolated use of the available sensors and to fulfil demanding safety requirements. In this paper a real application of data fusion for road safety for pedestrian detection is presented. Two sets of automobile-emplaced...
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