Traffic planning

The following applications arise in the field of traffic planning:

  • The mathematics behind traffic and environmental prediction is the same used in modern data mining. Therefore the development of mathematical models for traffic and environmental prediction can also be used to identify and quantify the principle dependencies and correlations in the traffic flows of a city.
  • The requirements management is used at all levels of the control hierarchy for the explicit collection and definition of the relevant traffic situations and the assignment for the desired traffic measures. These can then also be used for the direct training of the control objects. Thus traffic planning has direct influence on traffic control, by defining the control targets, which really can be followed.
  • Different traffic measures can be assessed and rated with the system rating as regards their effectiveness in traffic. This allows a controlled and targeted development of the right measures.
  • The new and flexible possibilities in the node, line, and net control through the simple definition and integration of new control actions and traffic measures allow an early consideration already in the planning and concept phase. A quick realization is already available at prototype level with realistic and performing functionality.
  • Incident detection can be used to identify and treat traffic situations, which have not already been considered for the calibration of the control but should have been considered. This is the basis for systematically grasping all the relevant traffic situations, which are used to train and adapt the control objects for steady improvements within the operation of the traffic control systems.
  • The example-based representation of the functional requirements for traffic control within the requirements management enables the quick and early identification, quantification and treatment of requirement conflicts. This normally leads to a much more consistent and realistic specification of the desired functionality resulting in less complex solutions with reduced efforts in development and implementation.