Hajmohammadi, H;
Marra, G;
Heydecker, B;
(2019)
Data-driven models for microscopic vehicle emissions.
Transportation Research Part D: Transport and Environment
, 76
pp. 138-154.
10.1016/j.trd.2019.09.013.
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Abstract
In this paper, a new approach for describing the relationship between tailpipe emissions and vehicle movement variables is presented, called generalized additive model for location, scale and shape (GAMLSS). The dataset for this model is second-by-second emission laboratory measurements, following a real driving cycle that were recorded in urban, suburban and motorway areas of London. The GAMLSS emission model estimates each of CO_{2}, CO and NO_{x} in each second for two different vehicle types (petrol or diesel) using instantaneous speed and acceleration as the explanatory variables. Comparing the results with current emission models indicates substantial improvement in accuracy and quality of estimation by this approach.
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