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handle: 11572/98034 , 11379/524284
Driving vehicles in platoons has the potential to improve traffic efficiency, increase safety, reduce fuel consumption, and make driving experience more enjoyable. A lot of effort is being spent in the development of technologies, like radars, enabling automated cruise control following and ensuring emergency braking if the driver does not react in time; but these technologies alone do not empower real platooning. The initial idea of building dedicated infrastructures for platoons, has been set aside favouring the philosophy that foresees scenarios, where automated vehicles share the road with human-driven ones. This arises interesting new questions regarding the interactions between the two categories of vehicles. In this paper we focus on the analysis of interferences caused by non-automated vehicles during a JOIN maneuver. We define the application layer protocol to support the maneuver, together with situations that can prevent successful termination, and describe how they can be detected. The validity of the approach is proven by means of simulations, showing either that the maneuver can successfully be performed, or safely be aborted. Finally, we analyze the impact of the Packet Error Rate (PER) on the failure rate of the maneuver, showing that packet losses mainly affect the maneuver from a coordination point of view, rather than stability of the system, i.e., even at high loss rates, cars never violated a minimum safety distance.
Platooning, Cooperative Driving, Vehicular Communications
Platooning, Cooperative Driving, Vehicular Communications
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 56 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
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