Victoria Main Roads Pilot Study

March 21, 2023
5 min read

Traditionally Star Rating of roads has been undertaken using imagery/video footage of the road system and manual coding. There are numerous Inspection Systems globally that have been accredited by iRAP for use for this purpose.
In October 2021, Anditi got accreditation for its Roadviewer Inspection System which was the first system globally to be accredited to use video/imagery and LiDAR. This system is designed to help facilitate the transition from manual iRAP coding using video through to accelerated and intelligent coding using LiDAR and imagery.

In late 2021 to early 2022, Anditi was commissioned by iRAP to assist in researching the application of accelerated and intelligent techniques for safety Star of Roads. The outcomes of this project are set out in a report ‘AiRAP Automation for Australian Road Safety’ which was prepared as part of an iMOVE project for Transport for NSW (TfNSW). This pilot project used a range of automated and semi-automated techniques to assess road safety attributes along the road network. Attributes were recorded for each 100 m road segment. This information was then used to generate coding data required for iRAP/AusRAP Star Rating of roads with the information being provided in iRAP VIDA compatible format.
The iMOVE project drew upon the findings of 2019 and 2020 pilot studies Anditi undertook for Main Roads Western Australia. The first of these projects explored ways to visualise and make accessible mobile LiDAR and 360 degree imagery of the road system using a web based portal. The second utilised accelerated and intelligent techniques combined with mobile LiDAR and 360 degree imagery acquired from TomTom, to identify and code 13 iRAP Star Rating attributes for 2000 km of roads across 7 regions in Western Australia. Outputs from this project were made available to Main Roads via a web portal and as shape files.

As part of the ‘AiRAP Automation for Australian Road Safety’ project, Anditi worked with iRAP in developing and proving the AiRAP Star-Rating assessment framework. During the course of this project, Anditi obtained AiRAP accreditation for 34 Star Rating attributes.
Development of this AiRAP framework:
• Provides the framework for converting new and emerging data sources into iRAP-compliant data for Star Rating.
• Is supplier independent and supports the accreditation of multiple data providers and analytical approaches to generate data that meets the iRAP global standard.
• Has a flexible process which accommodates data derived from different types of source data, as well as different collection and processing methods.
The AiRAP accreditation process accredits the process rather than an individual responsible for coding of the data. In so doing it provides end-users with the confidence that the source data and analytical approach for generating attributes in accordance with the iRAP global standard is viable and repeatable. It also provides an understanding of the reliability of the data for different geographic regions, area types and road types, as well as when and how the data should be used.
This project (5 Roads AiRAP Pilot Study) has also used remote sensing data (mobile LiDAR and imagery acquired from TomTom) to identify and locate safety attributes along the road system. As set out in Table 2, the project has extended the number of attributes being extracted from this data using accelerated and intelligent techniques.

As part of this project, further work with iRAP has been undertaken developing AiRAP attribute definitions. This been required to ensure that attributes are suitably detailed and defined to enable the use of automated techniques for accelerated and intelligent extraction of road safety attributes. iRAP.
This includes exploring ‘Digital Definitions’ of attributes such as:
• Skid resistance and road condition
• Quality criteria (i.e. quality of curvature, delineation, intersection, pedestrian crossing etc)
• Curvature, sight distance, skid resistance where the automated techniques used in AiRAP provide the opportunity for greater gradation between attribute categories. This could reduce the impact on Star rating of crossing from one threshold to another.
It has also involved exploring with iRAP how to code gaps in passenger side, median and driver side safety barriers and the impact of this on coding of carriageway type, intersections, property access, paved shoulder width and pedestrian fencing. This work is ongoing.


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