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Losada, AngelCorresponding AuthorPáez, Francisco JavierAuthorLuque, FranciscoAuthorPiovano, LucaAuthorSanchez, NuriaAuthorHidalgo, MiguelAuthor

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May 26, 2024
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Vehicle-to-Cyclist Collision Prediction Models by Applying Machine Learning Techniques to Virtual Reality Bicycle Simulator Data

Publicated to: Applied Sciences-Basel. 14 (9): 3570- - 2024-05-01 14(9), DOI: 10.3390/app14093570

Authors:

Losada, Angel; Paez, Francisco Javier; Luque, Francisco; Piovano, Luca; Sanchez, Nuria; Hidalgo, Miguel
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Affiliations

Univ Politecn Madrid, Ctr Energy Efficiency Virtual Real Opt Engn & Biom, Pozuelo De Alarcon 28223, Spain - Author
Univ Politecn Madrid, Univ Inst Automobile Res Francisco Aparicio Izquie, Madrid 28031, Spain - Author

Abstract

The study of vulnerable road users (VRUs) behavior is key to designing and optimizing driving assistance systems, such as the autonomous emergency braking (AEB) system. These kinds of devices could help lower the VRU accident rate, which is of particular interest to cyclists, who are the subject of this research. To better understand cyclists' reaction patterns in frequently occurring collision scenarios in urban environments, this paper focuses on developing a virtual reality (VR) simulator for cyclists (VRBikeSim) that incorporates eye-tracking functionality. The braking and steering systems were calibrated by means of on-track tests with a sensorized bicycle in order to improve the accuracy of the bicycle virtual model. From the data obtained in the virtual tests, a battery of predictive models was built using supervised machine learning classifiers. All of them exhibited an accuracy higher than 85%, especially the K-Nearest Neighbors model. This model allowed us to obtain the best balance between the prediction of avoidance and collision cases, as well as enabling computationally lower times to be incorporated into the decision-making algorithm of an AEB system.
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Keywords

Autonomous emergency braking (aebAutonomous emergency braking (aeb)CollisionMachine learningPerformance metricsPredictive collision modelVirtual reality cyclist simulator (vrbikesim)Vulnerable road users (vrus)

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal Applied Sciences-Basel due to its progression and the good impact it has achieved in recent years, according to the agency WoS (JCR), 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 50/179, thus managing to position itself as a Q2 (Segundo Cuartil), in the category Engineering, Multidisciplinary. Notably, the journal is positioned en el Cuartil Q2 para la agencia Scopus (SJR) en la categoría Engineering (Miscellaneous).

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 2026-04-06:

  • WoS: 2
  • Scopus: 3
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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 2026-04-06:

  • 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: 28 (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.
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    Leadership analysis of institutional authors

    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 (LOSADA ARIAS, ANGEL) and Last Author (HIDALGO MONJARDIN, MIGUEL).

    the author responsible for correspondence tasks has been LOSADA ARIAS, ANGEL.

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    Awards linked to the item

    This study benefited from the research activities developed by INSIA-UPM and CEDINT-UPM.
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