Browsing by Author "Northrop, William F"

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    Metro Transit Diesel Bus Engine Measurement Data for 19 Days in Winter 2014 in Minneapolis-St. Paul, MN, USA
    (2019-03-05) Kotz, Andrew J; Northrop, William F; alixx464@umn.edu; Ali, Reem Y; University of Minnesota Spatial Computing Research Group
    A sample engine measurement dataset for a diesel Metro Transit bus on three different routes in Twin Cities, MN. The data represents 19 days of operation in winter 2014.
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    Vehicle Emissions Prediction with Physics-Aware AI Models: Technical Report
    (2020) Panneer Selvam, Harish; Li, Yan; Wang, Pengyue; Northrop, William F; Shekhar, Shashi
    Given an on-board diagnostics (OBD) dataset and a physics-based emissions prediction model, this paper aims to develop an accurate and computational-efficient AI (Artificial Intelligence) method that predicts vehicle emissions values. The problem is of societal importance because vehicular emissions lead to climate change and impact human health. This problem is challenging because the OBD data does not contain enough parameters needed by high-order physics models. Conversely, related work has shown that low-order physics models have poor predictive accuracy when using available OBD data. This paper uses a divergent window co-occurrence pattern detection method to develop a spatiotemporal variability-aware AI model for predicting emission values from the OBD datasets. We conducted a case-study using real-world OBD data from a local public transportation agency. Results show that the proposed AI method has approximately 65% improved predictive accuracy than a non-AI low-order physics model and is approximately 35% more accurate than a baseline model.