Safe Driving Is Sustainable Driving: An Interpretable Telematics Methodology

Abstract

Driving remains one of the riskiest daily activities, contributing to 1.3 million fatalities each year. Separately, reducing emissions is crucial for mitigating climate change and protecting public health. In this study, we address these two critical issues by developing an analytical model to understand how safe driving behaviors align with sustainable driving behaviors, as measured by telematics. Telematics-enabled usage-based insurance financially incentivizes drivers to avoid dangerous behaviors by gathering sensor data and providing feedback on risky behaviors, including hard braking, speeding, and distraction. The sensor data used to measure safe driving can also be leveraged to predict fuel consumption, offering a detailed analysis of how driving behavior affects fuel use beyond just the distance driven. By applying four distinct fuel consumption models to a large corpus of telematics trips, we present a method to link safe driving practices to efficient driving practices. First, we show that safe driving behaviors are predictive of fuel consumption using an interpretable multiple variable regression analysis. Then we illustrate how changes in safe driving performance are associated with changes in efficient driving performance for a given driver. Specifically, we show that midrange drivers who improve their safety performance while participating in a telematics program achieve higher fuel efficiency compared with those who regress. This improvement amounts to 6% of the yearly environmental performance assessment-rated gasoline consumption, equating to 36.6 gal, for a Jeep Grand Cherokee. Our findings indicate that promoting safe driving habits can simultaneously advance sustainability goals, highlighting a dual benefit in policy and practice.