The Transportation Research Board (TRB) has called for tenders in an innovative AiRAP pilot to leverage artificial intelligence and big data to enhance road safety analysis in US networks, with expected global benefit.
The 30-month research programme aims to advance the use of artificial intelligence (AI) and machine learning (ML) in analysing big data and unconventional data to assess their effectiveness to support safe system and modal priority decision-making as well as road safety performance tracking.
The absence of low-cost data, safety performance metrics, and prioritized investment options make it difficult for agencies to understand the business case for safer roads and to measure progress.
The accelerated and intelligent coding of these attributes can provide significant savings and deliver the scale and frequency of data collection and analysis to support comprehensive performance tracking over time.
AiRAP captures the advances in AI, ML, vision systems (street and sky), light detection and ranging (LiDAR), telematics, and other data sources to deliver critical information on road safety, crash performance, investment prioritization, and RAP’s Star Rating of roads for pedestrians, cyclists, motorcyclists, and vehicle occupants.
The research will identify potential data sources, identify or develop the requisite data preparation and extraction algorithms for use in safety analysis, and document each source’s coverage, frequency of collection, granularity, accessibility to practitioners, and cost.
The data will allow the potential for lower-cost and more frequent generation of, among others: key fatality and injury prediction risk maps; road feature mapping; star ratings and other safety analyses for pedestrians, cyclists, motorcyclists, micro-mobility services, and vehicle occupants; identification of data for safety analyses and associated tools; and the development of safety plans that can be used for funding submissions and in prioritizing investments across the local and state road networks.
The pilot will develop guidance for managing data using a format that can be accessed by various tools and results may be included in national-level resources such as the AASHTO Highway Safety Manual and other tools that support data-driven safety analysis.
Further information on the pilot and requirements can be found here and proposals are due no later than 5:00pm US Eastern Time on 13 September 2021.
This research will build on the AI innovations under development globally for Road Assessment Programmes (RAP) in other countries.
For further information on AiRAP, visit https://irap.org/project/ai-rap/