Abstract
The current best practice for driving scoring is a simple Red, Amber, and Green (RAG) report. Our industry has pioneered much progress in land transport safety using the RAG scoring system and driver monitors - it served us well. But the coaching that management can provide through the RAG scoring is limited to the parameters that make up the score. For a complete understanding of driver behavior, the scoring system should take into account more sources of data: speed with respect to the current speed limit (speed by street), speed with respect to the vehicle type (speed by truck), the frequency of activation of the OEM safety systems (ABS, Traction Control, Lane Departure Warning) if installed, fatigue warnings and fitness for duty, journey characteristics, weather and road hazards, and more. We submit it is possible to understand and effectively coach drivers on a much deeper level with about the same amount of time and effort used in the current RAG best practice.
In this paper, we propose a next-generation best practice scoring framework for understanding and coaching at-risk driving behavior. The goal of this new algorithm is to rank drivers "apples to apples" with respect to safety even though their driving world is an "apples to oranges" world. The best practice will adapt to various vehicle types and installed safety equipment such as ABS, traction control, and stability control. It will provide a framework wherein key driving performance metrics such as speed by street can be seamlessly substituted with less-effective top-speed-only metrics. It shall be independent of the manufacturer of the driver monitor. And most importantly, the framework shall provide managers and HSE professionals with more analytical insight.
We analyze real driving histories of oilfield service trucks to explore the strengths of the proposed algorithm. Examples include safe, at-risk, and risky driver histories with long and short driving hours logged on various equipment. By comparing and contrasting analysis with the RAG method, the reader will understand the insight gained into driving behavior and the subsequent opportunities to take driving coaching to the next level.
