People and their communities are looking for transportation solutions that reduce travel time, improve well-being and accessibility, and reduce emissions and traffic congestion. Although new mobility services like ride-hailing advertise improvements in these areas, closer inspection has revealed a discrepancy between industry claims and reality. Key decision-makers, including citizens, cities and enterprise, and mobility service providers have the opportunity to leverage connected vehicle and connected device data through cloud-based APIs. We propose a GHG data analytics framework that functions on top of a cloud platform to provide unique system-level perspectives on operating transportation services, from procuring the most environmentally and people friendly vehicles to scheduling and designing the services based on data insights. The motivation behind such an approach is two-fold: first, quantification enables transparency to build trust between the mobility service provider and their constituent communities; and second, identifying and acting to improve sustainability improves profitability. Using a benchmark problem with real-world vehicle and mobile device data, we demonstrate the functionality of our GHG analytics framework.
