Since 2013, the Ministry of Transportation Ontario (MTO) has been making the transition from
manual to fully automated network pavement condition data collection, detection and distress
characterization using a new generation of Automated Road Analyzer (ARAN) equipped with
Laser Crack Measurement Systems (LCMS) and associated software. The ARAN’s
subsystems are configured to measure, record and provide continuous output for multiple data
streams. Pavement condition data collected by MTO’s ARAN is recorded and processed using
the Pave3D software suite.
Subsystems discussed in this paper include the high speed inertial profiler that measures and
report the pavement roughness as International Roughness Index (IRI) and automated LCMS
systems that capture rutting, cracking and macrotexture data. The new MTO ARAN subsystems
are capable of providing accurate and repeatable measurements of pavement distresses. A few
distresses such as raveling, flushing, shoving and distortion are detected by the ARAN
subsystems but the distress categorization algorithms are under development or being
completed.
In the interim, the ministry has developed three DMI and three PCI formulations based on
manual, automated LCMS and a combination of manual and automated LCMS rating datasets.
Comparison and validation analyses of these formulations were performed using data collected
from 934 pavement segments surveyed both by manual visual and automated LCMS methods.
Conversion of automated LCMS distress rating into equivalent manual distress rating is
presented. This conversion is necessary to provide compatible distress rating value for the
existing PMS/AMS system to function.
This paper presents the development and validation of the interim pavement performance
indices obtained using the various combinations of manual and automated distress datasets
and rating formulations.
Automated LCMS distress data collection changed the way how some pavement distresses are
detected, characterized, evaluated and reported. An opportunity exists as part of this transition,
to use selective automated LCMS metrics that will provide harmonization of metrics used and
direct linkages between metrics measured and pavement performance in the pavement design,
contract specification, construction acceptance, maintenance and pavement management
activities.
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