Individual Ratings
Ratings and Weightings
SimVT provides the flexibility to calculate ratings using different methods available in the rating method dropdown in the Correlation Setup Window. The resulting rating scores are color-coded differently depending on the protocol that is selected in the protocol dropdown in the Correlation Setup Window. It’s important to note that when you select a protocol, SimVT automatically applies the corresponding rating method associated with that protocol. However, this default selection can be overridden if you wish to use a different rating method. This ensures that while protocols streamline the rating process, you still have the control to adjust the methodology as needed.
Sensor Scores
The virtual testing protocols specify validation criteria which must be met in order to validate a simulation model. The criteria is generally a threshold score which must be met or exceeded for each assessed sensor. Sensor scores are derived from one or more component channels. For most sensors where X, Y and Z components are combined, Euro NCAP and C-NCAP adopt a consistent method or computing the sensor scores. First, weight factors, 𝑤𝑖, are calculated for each axis based on the maximum amplitude of the axis:
\(w_i = \frac{max(|Channel_{test_i}|)}{max(|Channel_{test_x}|) + max(|Channel_{test_y}|) + max(|Channel_{test_z}|)}\) with \(i = X, Y, Z\)
The overall sensor score is then computed with the equation:
\(S_{Sensor} = \displaystyle\sum_{i} w_i * S_i\) with \(i = X, Y, Z\)
The sensor scores are displayed in the "Sensor" column and the weight factors are presented in the "Weight" column so that the relative contribution of the individual axis ISO scores, 𝑆𝑖, to the overall sensor score, 𝑆sensor , is clearly visible
Some sensor scores are derived in a different way. For example, in the C-NCAP Far Side protocol the Head Offset sensor score is simply the average of the Y and Z offset component ISO Scores.
The thresholds for each sensor score also differ between the Euro NCAP and C-NCAP protocols. SimVT automatically configures the thresholds which are used for each sensor based on the selected protocol option and the sensor scores in the table are coloured coloured green and red to indicate if the sensor score exceeds the threshold (pass) or is less than the threshold (fail) respectively. Some channels are only monitored (i.e. they do not need to pass for the model to be validated) and they are coloured with pale green and pale red to indicate this.
The hover text on each sensor score entry reveals more information of how a sensor score was calculated.
Or, if the sensor score could not be calculated it will be displayed with a "?" and the hover text will provide details of any channel data which was expected but found to be missing.
For any channels which are not applicable to the selected protocol (or if no protocol is selected), the sensor score is un-weighted (i.e. it is the ISO score) so the weighting column entry will show "N/A". The colour bands used for the sensor score are consistent with those used for the individual ratings for non-protocol channels.
Individual Ratings
By default, the individual Corridor and Cross Correlation ratings are minimised to reduce the amount of space the Correlation Table occupies, but they can be shown by clicking the expander.The total rating is the weighted sum of the Corridor and all Cross Correlation ratings, with the weights depending on your selected correlation method.
For protocol channels (i.e. channels which mentioned as mandatory or monitored in the protocol), the ratings are coloured green and red to indicate if the rating exceeds the threshold (pass) or is less than the threshold (fail) respectively.
The ratings scores are coloured differently depending is they contribute to a mandatory or monitored protocol sensor or if the sensor is not specified by the selected protocol.
Mandatory protocol channels:
- rating >= threshold: green
- rating < threshold: red
- rating >= threshold: pale green
- rating < threshold: pale red
For non-protocol channels:
- rating >= 0.94: green
- rating >= 0.80: yellow
- rating >= 0.58: orange
- rating < 0.58: red
Filtering Ratings
To help you navigate and analyse results more efficiently, SimVT includes dropdown boxes similar to those in Excel for filtering ratings. When filters are applied, rows that do not meet the selected criteria are hidden from view. These dropdowns allow you to filter by various rating thresholds (e.g., pass/fail, with min/max values, etc). This feature improves usability, especially when working with large datasets, and ensures that you can quickly identify areas of interest or concern. To access them, right click on the header above a rating column (e.g. ISO). Below is an image with the popup visible for the ISO column:
The rating categories available include Excellent, Good, Fair, and Poor, and Pass and Fail (available when the protocol is set). The optional Pass and optional Fail filter checkboxes are displayed with brackets around them. There is also an Invalid checkbox which can be used to filter out any rows with any scores that had issues in obtaining the result. For ease of use, only the relevant checkboxes are active (ungreyed) when the popup appears. Additionally, you can set the Min and Max values to limit values between a certain threshold. You can use the Clear Filters button to remove all applied filters and restore the full dataset. Directly beneath this, a Close button allows users to exit the filter popup.
Below is an example of the Correlation Table without any filters applied on it:
And here is an example when a filter is applied on the ISO rating column:
The row with the optional "Pass" result no longer appears in the ISO column because it was filtered out by unchecking the (Pass) checkbox. To indicate that a filter is applied to a column, the white triangle next to the column header changes to a green filter icon whenever any filter setting deviates from its default. This is shown in the image above.
If filtering results in no visible rows, SimVT will display a warning message to inform the user that all entries have been filtered out. This helps distinguish between an empty dataset due to filtering and one caused by missing or invalid data.
Time of poorest correlation and Start of divergence
Time of poorest correlation is shown with background colour correlation zone it falls into.
Start of divergence is shown with white background.
If the whole sim curve is within inner corridor the we show N/A with grey background.