Study of the Impact of Cooperative Maneuvers Among Different Types of Vehicles in Real-World Scenarios

dc.contributor.authorMendes, Bruno
dc.contributor.authorGoes, Adriano
dc.contributor.authorAraújo, Marco
dc.contributor.authorCorujo, Daniel
dc.contributor.authorOliveira, Arnaldo S. R.
dc.date.accessioned2026-01-30T11:31:08Z
dc.date.available2026-01-30T11:31:08Z
dc.date.issued2025-08-01
dc.description.abstractThe automotive sector has seen a significant increase in autonomous mobility expenditures throughout the past decade through private-sector investments made by original equipment manufacturers and public research via universities and institutes. However, despite the significant funds invested in enabling technologies, the world is not much closer to self-driving vehicles on its main roads. One of the reasons for this is the lack of willingness to regulate this sector, as it requires taking accountability for failures. Moreover, to ensure the existence of autonomous vehicles (AV) on the road, regulation must be pushed, ensuring that both non-autonomous and AV can coexist. The lifespan of a vehicle can range from fifteen to thirty years on average. So, considering that classic vehicles still represent almost all vehicle sales, self-driving vehicles will share the roads in the next few decades. This implies that AVs must be able to adapt themselves to the behavior of human drivers and hold mechanisms to handle the higher probability of collisions and jams. Only once this adaptation is proven successful can regulation finally be implemented. This article explores how 5G, V2X, and intelligent transportation systems can make AV decisions safer by mitigating mixed-traffic vulnerabilities through V2V information exchange. Mathematical modeling and simulations such as Markov chains, Bayesian networks, and Monte Carlo simulations were used to quantify impact. Simulations modeled how non-AVs and AVs interact and estimate the probability of accidents and congestion across cooperation levels. Additionally, fleet composition dynamics were analyzed to assess accident rates and traffic flow as AV fleets grow. The results confirm that cooperation is imperative. Cooperative strategies significantly reduce crashes and optimize traffic flow at lower AV adoption. Complete autonomy is a challenging objective to obtain in the near-term future, and, under this study, cooperative integration between non-AVs and AVs must occur in a phased manner.
dc.identifier.citationMendes, B., Goes, A., Araújo, M., Corujo, D., & Oliveira, A. S. R. (2025). Study of the Impact of Cooperative Maneuvers Among Different Types of Vehicles in Real-World Scenarios. In 2025 International Conference on Computer, Information and Telecommunication Systems (CITS), Colmar, France, 16-18 July 2025, (pp. 1-8). IEEE. https://doi.org/10.1109/CITS65975.2025.11099223.. Repositório Institucional UPT. https://hdl.handle.net/11328/6927
dc.identifier.isbn979-8-3315-1437-2
dc.identifier.isbn979-8-3315-1438-9
dc.identifier.urihttps://hdl.handle.net/11328/6927
dc.language.isoeng
dc.publisherIEEE
dc.relation.hasversionhttps://doi.org/10.1109/CITS65975.2025.11099223
dc.rightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectAdaptation models
dc.subject5G mobile communication
dc.subjectRoads
dc.subjectMathematical models
dc.subjectRegulation
dc.subjectSafety
dc.subjectBayes methods
dc.subjectVehicle-to-everything
dc.subjectAutonomous vehicles
dc.subjectAccidents
dc.subject.fosCiências Naturais - Ciências da Computação e da Informação
dc.titleStudy of the Impact of Cooperative Maneuvers Among Different Types of Vehicles in Real-World Scenarios
dc.typeconference paper
dcterms.referenceshttps://ieeexplore.ieee.org/document/11099223
dspace.entity.typePublication
oaire.citation.conferenceDate2025-07-16
oaire.citation.conferencePlaceColmar, France
oaire.citation.endPage8
oaire.citation.title2025 International Conference on Computer, Information and Telecommunication Systems (CITS)
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.affiliation.nameREMIT – Research on Economics, Management and Information Technologies
person.familyNameAraújo
person.givenNameMarco
person.identifier.ciencia-id5910-B360-28A2
person.identifier.orcid0000-0002-0795-9981
person.identifier.scopus-author-id57923373300
relation.isAuthorOfPublicatione1d94704-8a55-4f06-b790-23c3d5c6ecc8
relation.isAuthorOfPublication.latestForDiscoverye1d94704-8a55-4f06-b790-23c3d5c6ecc8

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