Sentence examples for state of traffic from inspiring English sources

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Yandex Probki issues periodic white papers on the state of traffic, and maintains a blog with interesting traffic highlights, but its main task is to keep perpetually updated a now iconic three-color street map of the city, showing real-time traffic flow on a number of routes.

His anecdotes are enlightening (the girls exclaim with envy when told of an unmarried friend with an "elastic hymen" that seemingly never breaks) and, along the way, he conveys the sense and smell of Cairo, its hustle and humour, its near permanent state of traffic gridlock.

It is shown that there exists a state of traffic equilibrium.

The recovery ability represents the capacity of a city to recover and return to a normal state of traffic volume.

In order to obtain reliable information, the suggestions, based on the estimates of the predicted state of traffic conditions, should consider travellers' reactions to the information itself.

When CH touches the Threshold Area, as depicted on Fig. 8, it asks the state of traffic light from RSUs ((hbox {C}_{mathrm{sl}}, hbox {t}_{mathrm{sl}})).

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Therefore, during designing forwarding strategies for vehicular communication, the spatial-temporal states of traffic flow should be considered.

All of these schemes do not focus on improving forwarding performance according to different states of traffic flow, which will be addressed in this paper.

Based on their observations, the duo describe three states of traffic on busy highways: "free flow," in which traffic is light enough that drivers can freely change lanes and pass other cars; "synchronized flow," in which the roads are so clogged that drivers can't pass, but can still move; and jams.

Besides, the model is also capable of reproducing most empirical findings including the three states of traffic flow, the backward speed of the downstream front of the traffic jam, and different congested traffic patterns induced by a system with open boundary conditions with an on-ramp.

The prediction and identification of the states of traffic flow are important subjects in the field of intelligent transport systems [3, 4], since they can not only help drivers improve traveling efficiency through dynamic navigation, but also help optimize the performance of VANETs.

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