Maintaining thousands of kilometres of roads is a major expense and logistical challenge for Australian councils. Traditionally, much of this work is reactive – fixing potholes and cracks after they appear. Artificial Intelligence is paving the way for a shift towards proactive, predictive road maintenance, saving money and improving safety.
How AI Predicts Road Issues:
AI systems analyse data from various sources to forecast road deterioration before it becomes a major problem. This involves:
- Image Analysis: AI processes images captured by cameras mounted on vehicles (like council fleet vehicles or even waste trucks) to automatically detect defects such as potholes, cracks, faded lines, and damaged signs.
- Sensor Data: Information from sensors embedded in roads or vehicles can provide data on traffic loads, stress, and environmental conditions.
- Predictive Modelling: AI algorithms combine visual data, sensor data, weather patterns, and historical maintenance records to predict where and when defects are likely to occur.
Key Benefits:
- Optimised Maintenance Schedules: Prioritise repairs based on predicted need, not just current condition.
- Reduced Costs: Address minor issues before they become expensive major repairs.
- Improved Road Safety: Proactively fix hazards before they cause accidents.
- Minimised Disruption: Plan maintenance more efficiently to reduce traffic delays.
- Data-Driven Decisions: Allocate resources based on evidence and predictive insights.
Australian Initiatives Using AI for Roads:
- Noosa Council: Partnered with TechnologyOne and Retina Visions to use cameras on waste trucks for automated road defect detection. The AI software identifies and prioritises defects, integrating directly with their asset management system to create work orders automatically. This identified over 4,300 defects in just two months, shifting focus to preventative maintenance.
- Transport for NSW Asset AI Program: A state-wide initiative using cameras and AI to automatically detect and classify road defects. The platform assesses severity and provides data to councils for scheduling maintenance. Piloted with Canterbury-Bankstown and Griffith City Councils, it aims to expand state-wide, leveraging data for predictive insights and enhanced safety.
Supporting Resources and Technologies:
- Industry Support: The NRMA has welcomed initiatives like Asset AI, highlighting the need for predictive approaches.
- Commercial Solutions: Companies like Asset Vision, Vialytics, and Maintain-AI offer AI-driven tools for road condition assessment and defect detection.
- Industry Discussion: Publications like Pavement Australia discuss AI's transformative impact on road infrastructure management.
AI offers a powerful way for councils to move beyond reactive road repairs. By leveraging image analysis and predictive modelling, initiatives like those in Noosa and the NSW Asset AI program demonstrate how councils can achieve safer roads, optimised budgets, and more efficient maintenance operations through data-driven, proactive strategies.
Want to take predictive AI further across your council? Our comprehensive resource, *How to Apply AI Directives: A Practical Guide for Councils*, walks through responsible AI adoption across all departments — from infrastructure and road safety to customer service, planning, libraries, and more.