COST 354 Index

Purpose

To calculate a weighted condition index using the methodology set out in the European Cost 354 Study Report.

This index is in the form of a weighted sum but gives significantly more weight to the parameter with the greatest value. Details for the calculation can be found in the COST 354 Study Report (if you cannot find the study report on the formal site linked above, you can try this link).

The specifics of this method can be found on pages 39 and 40 of the report, with a worked example on P61.

Type Name

‘cost354_index’

Definition Syntax

‘[param1|param2] : [weight1|weight2] : [maxvalue] : [influencefactor]’

where:

  • ‘param1|param2’ denote the pipe-delimited list of keys mapping to values in the value dictionary.
  • ‘weight1|weight2’ denote the pipe-delimited list of weights to use in the index calculation. These weights can be constants (numbers), or they can be keys mapping to numeric values in the value dictionary.
  • ‘maxvalue’: is the maximum allowed value. Calculated values will be clipped to this value.
  • ‘influencefactor’ is the Influence Factor as defined and used in the COST 354 report.
Important

Currently, values you provide for weights, maxvalue and influence factor must be numbers.You cannot use a key in the value dictionary to represent these values. This functionality will be built into future versions. Let us know if this is something you need as a priority.

Example

‘par_lt_cracks_pct|par_mesh_cracks_pct|par_shoving_pct|par_potholes_pct : 0.2|0.3|0.3|0.2 : 100 : 20’

This setup code will create a JFunction that will take the values mapped to keys:

  • par_lt_cracks_pct (% longitudinal and transverse cracks)
  • par_mesh_cracks_pct (% mesh cracks, i.e. ‘crocodile’ cracks)
  • par_shoving_pct (% shoving)
  • par_potholes_pct (% potholes)

in the value dictionary and using weights 0.2, 0.3, 0.3 and 0.2.

The values and weights will then be used in the COST 354 index method with the resulting value restricted to a maximum of 100. The ‘20’ at the end of the setup code instructs JCass to use a value of 20 for the Influence Factor.

Comment

This function has been thoroughly tested using the examples given in the COST 354 report.