UC1_TC_11

* Preconditions: Detections generated by radar detection + tracking algorithm (including ML based post-processing/classification) shall match 99% of detections done by traffic camera based on LP detection and improve counting accuracy of the system in total. * Input conditions / steps: image/radar data from simulator/real-world containing thousands of passes of various vehicles (possibly including tricky traffic scenarios mentioned above). * Expected result: The radar shall match defined portion of detections with camera (in other words it should improve detection accuracy in most cases as counting accuracy of camera is mostly lower than 99%).

Test Case Id Use Case Number + Test Case Number For example: UC7_TC_1

Test Case Evaluation Criteria

Test Case V&V Method

Test Case Component Under Evaluation

VALU3S Framework

Evaluation Environment Type Type of environment where the method is applied. It can be more than one type of environment.(Dimension 1)

Evaluation Type Type of evaluation performed with that method. If a method is hybrid, more than one type can be selected.(Dimension 2)

Type of Component Under Evaluation Type of components that can be evaluated with that method. It can be more than one type.(Dimension 3)

Evaluation Stage The evaluation stage where the method is used.(Dimension 5)

Purpose of the Component Under Evaluation The type of purpose that can be evaluated by a method. It can be more than one type.(Dimension 6)

Type of Requirement Under Evaluation The type of requirements that a method is able to evaluate. It can be more than one type.(Dimension 7)

Evaluation Performance Indicator The type of evaluation criteria or KPI that a method is able to improve. It can be more than one type.(Dimension 8)

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