Matlab and Python codes for the computation of International Roughness Index (IRI) provided with our paper F. Sroubek, M. Sorel, J. Zak: Precise International Roughness Index Calculation. Int. J. Pavement Res. Technol. (2021).
If you use this code in your academic work or any work with publicly available reports, please cite our paper according https://doi.org/10.1007/s42947-021-00097-z. The paper can be found also on our page http://www.utia.cas.cz/biblio?pub=0545847.
The Python version contains a command line tool to work directly on files with profile data.
The core function iri (in iri.m for Matlab and iri.py for Python) contains the implementation of three methods: original Sayers' method, using numerical solver ode45 and the method from our paper. Our method works directly for irregular sampling and regular sampling with shifted starting position. In the Python version, we have not implemented the second option (numerical solver ode45), which is too slow to be used in practice. The python version can be also called as a command line script.
There are two example profiles in the repository:
- profile_1.txt ... regular sampling 0.25m
- profile_2.txt ... irregular sampling of the same profile (artifically computed by interpolation from profile_1.txt)
You can run four Matlab examples
- example_1.m ... regular sampling, no overlap, 20m IRI segments
- example_2.m ... regular sampling, step 0.5m, 20m IRI segments
- example_3.m ... irregular sampling, no overlap, 20m IRI segments
- example_4.m ... irregular sampling, step 0.5m, 20m IRI segments
To run the Python version, please make sure that you have installed the packages numpy, scipy and matplotlib (in requirements.txt). The command line interface has the same parameters as the core function, except that
- both the input and IRI output are contained in text/csv files.
- you can plot an IRI graph to a separate graphical file (pdf, png, svg, etc.).
- parameter box_filter of the function iri in iri.py is replaced by parameter -filter_off on the command line
For the description of command line parameters, see its help by running
python iri.py -h
Examples of command line use:
python iri.py ../profile_1.txt testdir/iri_file.txt -plot_file testdir/plot_file.pdf
python iri.py ../profile_2.txt testdir/iri_file2.txt -plot_file testdir/plot_file2.svg -step 0.25
function IRI = iri(Y, segment_length, start_pos, step, box_filter, method)
Input:
Y ... road profile, two-column matrix [x,y], both distance x and elevation y must be in meters to get the iri in [mm/m].
segment_length ... length of the IRI segment (typically 20 or 100 meters)
start_pos ... starting position of IRI segments, if empty, set to the first sample
step ... if empty, false or 0, IRI is computed in segments without overlap, otherwise, the step is the shift of consecutive IRI segments (can be set for example to a multiple of sampling step for regular sampling); overlap cannot be logical true.
box_filter ... true/false (impl. value true), if true, profile is first averaged with a box filter of length 0.25m as recommended in Sayers' paper for sampling intervals shorter than 0.25m to better represent the way in which the tire of a vehicle envelops the ground.
method ... 0 - Sayers' implementation, for regular sampling only, 1 - numerical solver ode45 (not implemented in Python), 2(default) - our semi-analytical solution (Sroubek & Sorel)
Output:
IRI ... IRI vector calculated in segments; matrix with rows [star_pos, end_pos, IRI, std_of_IRI], where std_of_IRI is standard deviation of IRI within each segment, IRI is in mm/m [equivalent to m/km]