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dynamic traffic
As we have indicated, the issue of what is optimal fairness under the dynamic traffic is open.
      
Behavior of a whole-link travel-time model used in dynamic traffic assignment.
      
Clearly this is a fleeting goal to aim for with any dynamic traffic assignment.
      
Computational Efficiency Dynamic traffic assignment models have been criticized for their computational inefficiency for large-scale real networks.
      
Clearly, more effort is needed before dynamic traffic assignment is recognized and accepted at the level of its static counterpart.
      
Comparing the two matrices, the benefit of Erlang dimensioning for dynamic traffic can be seen.
      
Consequently, the single request write time is a lower bound of the write time for the request size S under dynamic traffic.
      
Due to the fast movement of vehicles, and high dynamic traffic conditions, this situation is not uncommon.
      
Dynamic traffic refers to requests that are directed to some kind of Web application that generates the responses for each request.
      
Dynamic traffic is usually much lower than P2P traffic on public networks which are then less sensitive to its variations.
      
Dynamic traffic network models are such methods which have good potential to be applied for large-scale urban transportation networks.
      
Dynamic traffic assignment is concerned with solving for user equilibrium routing while treating departure times as given.
      
Dynamic traffic flow modeling has captured the focus of many researchers in the transportation area.
      
Dynamic traffic assignment and dynamic traffic control, Transportation and Traffic Theory, Edited by M.
      
Dynamic traffic lights do react on the traffic situations and it will alter its green, yellow and red periods on basis of actual traffic demands.
      
Dynamic traffic lights are usually based on calculations with computer models.
      
Dynamic traffic control is a traffic responsive control method that takes the variations of the traffic situation over time into account.
      
Dynamic traffic prediction is a must for predictive congestion control and buffer management.
      
Dynamic traffic demand was derived from the 15 minute counts using a dynamic synthetic O-D technique.
      
Furthermore, the test results have been separated depending if they are obtained with static or dynamic traffic.
      
 

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