Road maintenance investment decisions are conventionally made by experts with decades of experience. Those experts are often occupied by a heavy workload so they often have limited time to train new staff. The aim is to develop an efficient and robust data driven decision-making model for road maintenance investment planning to improve transparency and repeatability and minimise risks. The main objectives are to:
- Develop efficient and robust data driven decision-making model for road maintenance investment planning to improve the transparency and repeatability and minimise the risk.
- Capture experts’ knowledge using the machine learning models including the implicit decision rules they might use.