Big data and artificial intelligence can play a lead role in building the social and economic business case for safer roads and create the scale of change needed to save millions of lives. The accelerated and intelligent collection and coding of road attribute data has the potential to reduce the time and effort required to undertake road safety assessments, reduce the costs and improve accuracy.
Together with its road safety Star Ratings and fatality and serious injury estimation models, iRAP’s AiRAP initiative has the potential to put this road safety data at the fingertips of road authorities, policy-makers, investors and road users worldwide.
AiRAP aims to capture the advances in artificial intelligence, machine learning, vision systems, LIDAR, telematics and other data sources to deliver critical information on road safety, crash performance, investment prioritisation for all road users. The data would meet iRAP’s common global standard, which is already being used globally for recording of road features that impact road safety to streamline and benchmark performance.
The accelerated and intelligent coding of these attributes will also enable the scale and frequency of data collection to support comprehensive performance tracking over time. This will support decision-making and investment prioritisation on the scale needed to help meet the United Nation’s Sustainable Development Goal 3.6; To halve road deaths and serious injuries by 2030.
iRAP’s AiRAP initiative involves two principle elements:
- The AiRAP attribute accreditation will verify that source data converted into iRAP attributes meets iRAP’s stringent quality requirements and is scalable; That is, it can be consistently applied across specified geographic locations and road types.
- The AiRAP ‘Data Marketplace’ will connect those needing data with those supplying it.
How does AiRAP differ from current methods of data collection?
AiRAP methods are different from conventional RAP data collection methods, which typically require:
- Road surveys to collect video footage of the road (and collect traffic flow and speed data if this is not known)
- Road attribute coding using video data and manual coding teams, and
- Preparation of the data to enable it to be processed to produce Star Ratings and Investment Plans.
AiRAP will be able to complement or substitute the conventional methods used for road surveys, coding and supporting data collection. AiRAP attribute capture may or may not require a road survey depending on the type of source data being used. Source data is processed into a format compatible with the systems used to produce Star Ratings and Investment Plans.
AiRAP will be the conduit by which suppliers can provide access to and/or sell globally consistent source data and attributes via new channels to the market to help deliver faster, more affordable and more accurate data for the purposes of KPI reporting of individual iRAP attributes, iRAP Light Data Metrics, iRAP Star Ratings, Fatality Estimations and Safer Roads Investment Plans.
To support this, AiRAP attribute accreditation will ensure data meets iRAP’s global specifications and quality standards to ensure investors, decision-makers and road planners can continue to trust RAP results. This approach will also ensure harmonised data worldwide that will support a viable AiRAP market and local, national, regional and global benchmarking and performance tracking.
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Global Innovation Manager and Cities Specialist