Requirements Management

The main difficulties in “intelligent” traffic control are the often unknown and conflicting dependencies in the targets and requirement criteria. For the use of optimized traffic control methods a clear and consistent formulation of the control targets is crucial for the resulting functionality and performance. Inconsistent and conflicting requirements usually lead to significantly increased development and implementation efforts with reduced functionality and performance. Therefore the identification and quantification of requirement conflicts with accompanying processes for managing the resolutions is of highest priority in the early phase of the system specification.

ANDATA’s approach to solving traffic control offers a process with underlying software tools and methods for active requirements management for “intelligent” traffic solutions. By this we mean that it is clearly defined

  • which control actions are to be triggered when and how
  • in which traffic and environmental situations
  • based on which sensors and information.

These functional requirements are to be represented by examples from real readings or from simulations. The given data then build the basis

  • for an example-based system specification,
  • for a quick and early identification of requirement conflicts,
  • for a direct input to train the control functions.

Hereby also special simulation methods are offered for the definition and illustration of the desired control actions as well as an alternative course of action with respect to the resultant traffic values with performance criteria and sensor data. These show the dependencies and quantitative relations between the different criteria and traffic values with the different control targets and criteria.


Features and Advantages

  • Quantitative description of the dependencies and relations between the requirement and target criteria for traffic control.
  • Quick and early identification of conflicts in the requirements and target criteria, also showing options for the resolution of the conflicts.
  • Direct basis for the training and calibration of the control models.
  • Avoidance of extensive trial and error scenarios.
  • Controlled iterative improvements in the control results and systematic build-up and maintenance of expertise about the dependencies in traffic of a given city.