A seq2seq learning method for microscopic emission estimation of on-road vehicles
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 …
the pollution of on-road vehicles. Existing research has evolved from fitting nonlinear models …
A microscopic model of vehicle co₂ emissions based on deep learning—A spatiotemporal analysis of taxicabs in Wuhan, China
It is important to assess environmental impact of intelligent transportation systems, and
hence developing a vehicle emission model with high accuracy has been a long-standing …
hence developing a vehicle emission model with high accuracy has been a long-standing …
Estimating average vehicle mileage for various vehicle classes using polynomial models in deep classifiers
N Niroomand, C Bach - IEEE Access, 2024 - ieeexplore.ieee.org
Accurately measuring vehicle mileage is pivotal in precise CO2 emission calculations and
the development of reliable emission models. Nonetheless, mileage data gathered from …
the development of reliable emission models. Nonetheless, mileage data gathered from …
Rapid assessments of light-duty gasoline vehicle emissions using on-road remote sensing and machine learning
Y Xia, L Jiang, L Wang, X Chen, J Ye, T Hou… - Science of The Total …, 2022 - Elsevier
In-time and accurate assessments of on-road vehicle emissions play a central role in urban
air quality and health policymaking. However, official insight is hampered by the Inspection …
air quality and health policymaking. However, official insight is hampered by the Inspection …
Deep Learning-Based Mesoscopic Pollutant Emissions Modeling in Road Traffic Networks
Air pollution is a pressing global concern, particularly in urban environments, where
transportation systems contribute significantly. Enhancing air quality calls for effective …
transportation systems contribute significantly. Enhancing air quality calls for effective …
High-fidelity modeling of light-duty vehicle emission and fuel economy using deep neural networks
The transportation sector contributes significantly to emissions and air pollution globally.
Emission models of modern vehicles are important tools to estimate the impact of …
Emission models of modern vehicles are important tools to estimate the impact of …
Uj-flac: Unsupervised joint feature learning and clustering for dynamic driving cycles construction
Driving cycles construction, which aims to generate various vehicle driving profiles
corresponding to typical traffic conditions, plays an important role in the evaluation of vehicle …
corresponding to typical traffic conditions, plays an important role in the evaluation of vehicle …
Multi-component fusion temporal networks to predict vehicle exhaust based on remote monitoring data
X Fei, F Long, F Li, Q Ling - IEEE Access, 2021 - ieeexplore.ieee.org
Vehicle exhaust prediction is of great importance for exhaust emissions control and public
environment protection, and very challenging because it is influenced by various complex …
environment protection, and very challenging because it is influenced by various complex …
Modelling of instantaneous emissions from diesel vehicles with a special focus on NOx: Insights from machine learning techniques
CMA Le Cornec, N Molden, M van Reeuwijk… - Science of The Total …, 2020 - Elsevier
Accurate instantaneous vehicle emissions models are vital for evaluating the impacts of road
transport on air pollution at high temporal and spatial resolution. In this study, we apply …
transport on air pollution at high temporal and spatial resolution. In this study, we apply …
High-emitter identification for heavy-duty vehicles by temporal optimization LSTM and an adaptive dynamic threshold
Heavy-duty diesel vehicles are important sources of urban nitrogen oxides (NO x) in actual
applications for environmental compliance, emitting more than 80% of NO x and more than …
applications for environmental compliance, emitting more than 80% of NO x and more than …