ASAsense Documentation (staging) - User contributions [en]

PAVEsense - Export Formats/en

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PAVEsense data (formerly ''Roads AI'') can be exported from the portal in CSV and ESRI Shapefile format. Below is a list with the meaning of all fields.

We regularly refer to the SCCR indicators. These are the relative indicators macro1, macro2, mega1, mega2 and waviness.

For information on the interpretation of the indicators and the convergence criteria, see the [[PAVEsense/en#Kwaliteitsindicatoren|PAVEsense user manual]].

{| class="wikitable"
! CSV field name
! Meaning
|-
| recipe_id
| The version of the software used for the export. All data within the same recipe_id are comparable. SCCR indicators are not comparable when the recipe_id differs.
|-
| gen_date
| The date on which the export took place
|-
| month
| The month the data relates to
|-
| segment_id
| The internal ID of the road segment concerned
|-
| road_name
| The name of the road, if it exists and is known to the system
|-
| sccr_first
| The date of the oldest measurement used to determine the SCCR indicators
|-
| sccr_last
| The date of the most recent measurement used to determine the SCCR indicators
|-
| sccr_conv
| Have the SCCR values converged?
|-
| v_85_kmh
| The reference speed (85th percentile of the measured speeds)
|-
| macro1
| Macro1 indicator
|-
| macro2
| Macro2 indicator
|-
| mega1
| Mega1 indicator
|-
| mega2
| Mega2 indicator
|-
| waviness
| Waviness indicator
|-
| macro1_ns
| Macro1 indicator – non-scaled
|-
| macro2_ns
| Macro2 indicator – non-scaled
|-
| mega1_ns
| Mega1 indicator – non-scaled
|-
| mega2_ns
| Mega2 indicator – non-scaled
|-
| wavi_ns
| Waviness indicator – non-scaled
|-
| iri_first
| The date of the oldest measurement used to determine the IRI indicator
|-
| iri_last
| The date of the most recent measurement used to determine the IRI indicator
|-
| iri_conv
| Have the IRI measurements converged?
|-
| iri_min
| The minimum measured IRI
|-
| iri_50perc
| The 50th percentile of the IRI measurements
|-
| iri_85perc
| The 85th percentile of the IRI measurements
|-
| iri_max
| The largest measured IRI value
|-
| iri_avg
| The average IRI value
|-
| iri_sterr
| The standard deviation of the measured IRI values
|-
| iri_rq
| The driving quality (from Poor to Very Good)
|-
| iri_rq_int
| The driving quality (from 1 to 5, with 1 Poor and 5 Very Good)
|-
| surf_conv
| Have the surface determinations converged?
|-
| surf_best
| Most likely estimated surface type
|-
| surf_src
| The source used to determine the surface type '''(TODO: document the meaning of the sources)'''
|-
| geometry
| The geometry of the road segment, in [[wikipedia:Well-known_text_representation_of_geometry|WKT]]
|-
| authority
| The road authority responsible for this road segment
|}

PAVEsense - IRI Correlation/en

2026-10-14T12:07:49Z

FuzzyBot: Updating to match new version of source page

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[[File:Port of Antwerp Groundtruth vs eIRI measurements of ASAsense.jpg|thumb|eIRI ASAsense vs IRI reference]]

''Valid from PAVEsense version 8 (November 2024)''

The ASAsense eIRI values are calculated from the road profile measured with the accelerometer in the sensor box. We combine the measurements of the different passes and take the '''average''' eIRI of all passes that meet the [[PAVEsense/en#Convergentie|convergence criterion]].

==== Comparison with reference measurements in the Port of Antwerp ====

The correlation was made using reference data that we kindly received from the Port of Antwerp. After applying some corrections for GPS drift, we observe a correlation (R² factor) of 70%. Given that we measure after the damping of the vehicle and across several passes, whereas the reference data is recorded once and always along one side of the vehicle, we consider this a good correlation factor. More important, however, is the effect on the analysis. There is a very good similarity between the reference data and the ASAsense data: the worse roads in the reference data also come out as bad in the ASAsense data, and the good ones as good.

[[File:Distributie eIRI vs referentie.png|thumb|eIRI ASAsense compared with the PoA distribution]]

When we look at the overall distribution of the data, we also see a very strong agreement.

Below we have also compared the "driving quality" indicator with the reference measurements. We analyse this with a "confusion matrix", a standard approach for classification problems. Quality is mainly predicted in neighbouring quality labels, as the confusion matrix shows. For example, of the roads whose true label is "very good", 96% are predicted as "good" or "very good".

==== Development ====

===== PAVEsense version 8 =====

The alignment of the measured data was improved. As a result, peaks now coincide better at the correct location. This makes averaging over different passes a more effective way to obtain the final result. Moreover, it is a simpler method and also works when there are few passes over the same location. The following table shows the R² of the new version compared with the previous one. We also see that the prediction of ''Driving Quality'' has improved significantly compared with the previous version. The table was created with the same data for v7 and v8, which makes comparison possible.

{| class="wikitable"
! eIRI version
! R² (dtw-aligned)
|-
| PAVEsense v7 and earlier
| 0.61
|-
| from PAVEsense v8
| '''0.7'''
|}

[[File:Driving quality confusion matrix.png|thumb|eIRI driving quality confusion matrix, normalised on the true label]]

===== PAVEsense version 7 and earlier =====

In PAVEsense v7 and earlier, the 85th percentile was used to combine different passes into one measurement. This version under-reported the measured eIRI, so many roads ended up in a better category than in reality.

[[File:PAVEsense v7 driving quality confusion matrix.png|thumb|PAVEsense v7 (older software) driving quality confusion matrix, normalised on the true label]]

Main Page/en

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Welcome to the ASAsense documentation site. Here you will find all the information you need to use the ASAsense applications.

== PAVEsense ==

The [[PAVEsense/en|PAVEsense user manual]] explains how to assess and monitor road quality in the PAVEsense portal:

# [[PAVEsense/en#Inleiding|Introduction]]
# [[PAVEsense/en#Kwaliteitsindicatoren|Quality indicators]]
# [[PAVEsense/en#Convergentie|Convergence]]
# [[PAVEsense/en#Automatische_kalibratie|Automatic calibration and lead time for new data]]
# [[PAVEsense/en#Het_portaal|The portal]]
# [[PAVEsense/en#De_tabelweergave|The table view (Data table)]]
# [[PAVEsense/en#De_kaartweergave|The map view (Map)]]
# [[PAVEsense/en#Annotaties|Annotations]]
# [[PAVEsense/en#Exporteren|Exporting (Export)]]
# [[PAVEsense/en#Meetdekking|Measurement coverage (Coverage)]]
# [[PAVEsense/en#Veelgestelde_vragen|Tips and frequently asked questions]]

Further reading:

* [[PAVEsense - Export Formats/en|Export formats: meaning of the exported fields]]
* [[PAVEsense - IRI Correlation/en|eIRI correlation with reference measurements]]

== AMBIsense ==

* [[AMBIsense/en|AMBIsense: data formats and instant measurements]]
* [[ASAsense Binary Table (ABT) format/en|The ASAsense Binary Table (ABT) format]]

Translations:PAVEsense - IRI Correlation/3/en

2026-10-14T12:07:33Z