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Analysis of institutional authors

Rivera-Campoverde, Néstor DiegoCorresponding AuthorArenas-Ramirez, BlancaAuthorSanz, Jose Luis MunozAuthor

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April 21, 2024
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GPS Data and Machine Learning Tools, a Practical and Cost-Effective Combination for Estimating Light Vehicle Emissions

Publicated to:Sensors. 24 (7): 2304- - 2024-04-01 24(7), DOI: https://doi.org/10.3390/s24072304

Authors: Rivera-Campoverde, ND; Arenas-Ramírez, B; Sanz, JLM; Jiménez, E

Affiliations

Inst Univ Invest Automovil Francisco Aparicio Izqu, Univ Politecn Madrid UPM, Escuela Tecn Super Ingn Ind ETSII, Madrid 28006, Spain - Author
Univ Politecn Madrid UPM, Escuela Tecn Super Ingn Ind ETSII, Machine Engn Div, Madrid 28006, Spain - Author
Univ Politecn Salesiana, Grp Invest Ingn Transporte, Cuenca 010105, Ecuador - Author
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Abstract

This paper focuses on the emissions of the three most sold categories of light vehicles: sedans, SUVs, and pickups. The research is carried out through an innovative methodology based on GPS and machine learning in real driving conditions. For this purpose, driving data from the three best-selling vehicles in Ecuador are acquired using a data logger with GPS included, and emissions are measured using a PEMS in six RDE tests with two standardized routes for each vehicle. The data obtained on Route 1 are used to estimate the gears used during driving using the K-means algorithm and classification trees. Then, the relative importance of driving variables is estimated using random forest techniques, followed by the training of ANNs to estimate CO2, CO, NOX, and HC. The data generated on Route 2 are used to validate the obtained ANNs. These models are fed with a dataset generated from 324, 300, and 316 km of random driving for each type of vehicle. The results of the model were compared with the IVE model and an OBD-based model, showing similar results without the need to mount the PEMS on the vehicles for long test drives. The generated model is robust to different traffic conditions as a result of its training and validation using a large amount of data obtained under completely random driving conditions.

Keywords

Diesel passenger carsEmission parametric modelEmissions gasosesFuel consumptionLow-cost emission modelMachine learning modelNox emissionsOptimizationPerformancePortable emissions measurement systemReal driving emissionReal driving emissionsSpee

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal Sensors due to its progression and the good impact it has achieved in recent years, according to the agency Scopus (SJR), it has become a reference in its field. In the year of publication of the work, 2024 there are still no calculated indicators, but in 2023, it was in position , thus managing to position itself as a Q1 (Primer Cuartil), in the category Instrumentation.

Independientemente del impacto esperado determinado por el canal de difusión, es importante destacar el impacto real observado de la propia aportación.

Según las diferentes agencias de indexación, el número de citas acumuladas por esta publicación hasta la fecha 2025-10-15:

  • WoS: 2
  • Scopus: 7

Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2025-10-15:

  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 13 (PlumX).

With a more dissemination-oriented intent and targeting more general audiences, we can observe other more global scores such as:

    It is essential to present evidence supporting full alignment with institutional principles and guidelines on Open Science and the Conservation and Dissemination of Intellectual Heritage. A clear example of this is:

    • The work has been submitted to a journal whose editorial policy allows open Open Access publication.
    • Assignment of a Handle/URN as an identifier within the deposit in the Institutional Repository: https://oa.upm.es/90018/

    As a result of the publication of the work in the institutional repository, statistical usage data has been obtained that reflects its impact. In terms of dissemination, we can state that, as of

    • Views: 75
    • Downloads: 9

    Leadership analysis of institutional authors

    This work has been carried out with international collaboration, specifically with researchers from: Ecuador.

    There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: First Author (RIVERA CAMPOVERDE, NÉSTOR) and Last Author (Jimenez, Edisson).

    the author responsible for correspondence tasks has been RIVERA CAMPOVERDE, NÉSTOR.