In this paper, we introduce an open-source model" MOVESTAR" to calculate the fuel
consumption and pollutant emissions of motor vehicles. This model is developed based on …

The reduction of carbon emissions within the transportation sector is one of the most
important steps against the threat of global warming. Unless strict emissions-reduction and …

Road transport is a major contributor to world energy consumption and emissions. The
validity of models developed for environmental assessment of transport projects when used …

The automotive industry makes extensive use of virtual models to increase efficiency during
the development stage. The complexity of such virtual models increases with the complexity …

Microscopic emission estimation based on driving states plays a crucial role in controlling
the pollution of on-road vehicles. Existing research has evolved from fitting nonlinear models …

On-road carbon dioxide (CO2) emissions from light-duty diesel trucks (LDDTs) are greatly
affected by driving conditions, which may be better predicted with the sequence deep …

To confront the lack of robust and accessible models predicting diesel truck fuel
consumption, this study develops an Engine-based Correction Model (ECM) using a sample …

Driving is a complex task involving the perception of the driving event, planning response,
and action. Safe driving ensures the vehicle's and its passengers' safety, whereas …

1 Introduction in order to develop and evaluate transportation policy, agencies at the local,
state, and federal levels currently rely on the mobile source emission4factor models MOBiLE …

This paper presents a machine learning approach to model the electric consumption of
electric vehicles at macroscopic level, ie, in the absence of a speed profile, while preserving …