Machine learning helps Indiana DOT bundle projects -- GCN

The Indiana Transportation Department (INDOT) is applying machine learning (ML) to project bundling to maximize cost savings and reduce the time it takes to create bundles from a week to minutes. Transportation engineers typically group infrastructure construction projects into bundles to gain efficiencies in contracting and project management, minimize infrastructure disruption and achieve economies of scale. Bundles are created from similar projects – bridge projects, freeway lighting installations or safety improvements – or from a variety of types of work in a specific location. Bundling is complex, manual, subjective process, with engineers usually working from maps and spreadsheets. INDOT has done manual project bundling for about five years and used that data to test benefits of ML-enabled bundling, in which an algorithm that had been trained on historic data makes bundling suggestions.