Abstract—With the emergence of pervasive computing technologies into vehicles, driving has moved from an active task of steering towards an interaction or adaptation task with respect to the driver-vehicle feedback loop. Up to now vehicular interfaces have mostly been evaluated from a single-driver singlecar viewpoint, however, driving is a more complex task involving – beside the local interaction – the interrelationship between all the cars in a certain community of interest. The question investigated in this research work is how a vehicle’s local parameters in a bulk of cars (e. g. vehicle speed, braking parameters) affect the global behavior of this system (traffic congestion, driving speed variation, throughput). To explore this, two traffic models have been developed and simulated using the NetLogo simulation environment. Simulation results have shown that the intercar distance has a direct impact on both the throughput and the mean trip time. The proactive driving approach using vibro-tactile driver notification followed in the second, advanced model achieved much better results regarding these parameters compared to the simple manual-driven case. Finally, the outcomes legitimate the implementation of a prototype, and the installation of such a technology into a large number of cars in order to provide evidence for the improved traffic flow and decreased probability of traffic accidents in real driving scenarios
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