During the last year, the STEPS team developed empirically based tools to understand vehicle’s performance under various operation modes (minimum fuel consumption, minimum NOx or CO2). Moreover, the team developed a static eco-routing tool that considers such operating modes. The new research could implement these tools to identify zones (geofences) where NOx, or other emissions need to be minimized. In doing so, the tool can estimate the impacts on other operating characteristic parameters (e.g., fuel consumption). As part of this work, the team will expand the previous work by considering the probabilistic nature of network flow conditions in the estimate and model. This is important because the current version of the eco-routing system is based on speed-based vehicle performance functions, and uses static (historic) travel speeds. The team will estimate approximate speed probability distribution functions and consider when designing the routes. Additionally, the team will coordinate with the industry partners for the possibility of having access to other driving data (with emissions information) to validate the existing assumptions, and update the models if necessary.
This project could be starting point to the development of a monitoring and measurement project that includes data collection (OBD, GPS, PEMS) for different types of vehicles under different driving patterns, in a following research effort. The team has already developed a tool to use the data and estimate characteristic drive-cycles, which could be used to generalize the findings from the data collection. Doing this will be of great importance, because the research could shed light into the data and resource requirements to do in-use monitoring strategies.