Estimation of Areas with the Highest Accident Rate on the Cuenca-Loja Road According to the Driving Maneuvers

Néstor Rivera Campoverde; Paúl Molina Campoverde; Juan Molina Campoverde

doi:10.1007/978-3-031-24327-1_29

Estimation of Areas with the Highest Accident Rate on the Cuenca-Loja Road According to the Driving Maneuvers

Research Group in Transportation Engineering (GIIT)

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

Cuenca-Loja Road is a great reflection of the national reality, in the last five years, there have been 13 accidents of public transport vehicles, which left as consequences 159 injuries and 18 deaths. According to data from the National Traffic Agency (ANT) the main cause of accidents is the driver inexperience being 65.56% due to speeding, 23.33% due to invasion of the lane in an overtaking maneuver, and 11.11% for lost control of the vehicle. This research determines the areas with the highest accident rates along the Cuenca - Loja Road based on the physical characteristics of the road and the driving style. Fort the data acquisition a data logger device connected to the OBD II port was used that stores information such as speed, acceleration, and GPS, among others. Then, using automatic learning tools, the correlation between the different characteristics of the road (long slopes, road curves, etc.) and the driving style was determined in order to establish driving parameters appropriate to the geography and road surface.

Original language	English
Title of host publication	Intelligent Technologies
Subtitle of host publication	Design and Applications for Society - Proceedings of CITIS 2022
Editors	Vladimir Robles-Bykbaev, Josefa Mula, Gilberto Reynoso-Meza
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	335-345
Number of pages	11
ISBN (Print)	9783031243264
DOIs	https://doi.org/10.1007/978-3-031-24327-1_29
State	Published - 2023
Event	8th International Conference on Science, Technology and Innovation for Society, CITIS 2022 - Guayaquil, Ecuador Duration: 22 Jun 2022 → 24 Jun 2022

Publication series

Name	Lecture Notes in Networks and Systems
Volume	607 LNNS

Conference

Conference	8th International Conference on Science, Technology and Innovation for Society, CITIS 2022
Country/Territory	Ecuador
City	Guayaquil
Period	22/06/22 → 24/06/22

Bibliographical note

Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Driving behavior
Driving style
Machine learning
Traffic accidents

CACES Knowledge Areas

617A Design and Construction of Motor Vehicles, Boats and Aircraft

Access to Document

10.1007/978-3-031-24327-1_29

Cite this

Rivera Campoverde, N., Molina Campoverde, P., & Molina Campoverde, J. (2023). Estimation of Areas with the Highest Accident Rate on the Cuenca-Loja Road According to the Driving Maneuvers. In V. Robles-Bykbaev, J. Mula, & G. Reynoso-Meza (Eds.), Intelligent Technologies: Design and Applications for Society - Proceedings of CITIS 2022 (pp. 335-345). (Lecture Notes in Networks and Systems; Vol. 607 LNNS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-24327-1_29

Rivera Campoverde, Néstor ; Molina Campoverde, Paúl ; Molina Campoverde, Juan. / Estimation of Areas with the Highest Accident Rate on the Cuenca-Loja Road According to the Driving Maneuvers. Intelligent Technologies: Design and Applications for Society - Proceedings of CITIS 2022. editor / Vladimir Robles-Bykbaev ; Josefa Mula ; Gilberto Reynoso-Meza. Springer Science and Business Media Deutschland GmbH, 2023. pp. 335-345 (Lecture Notes in Networks and Systems).

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title = "Estimation of Areas with the Highest Accident Rate on the Cuenca-Loja Road According to the Driving Maneuvers",

abstract = "Cuenca-Loja Road is a great reflection of the national reality, in the last five years, there have been 13 accidents of public transport vehicles, which left as consequences 159 injuries and 18 deaths. According to data from the National Traffic Agency (ANT) the main cause of accidents is the driver inexperience being 65.56\% due to speeding, 23.33\% due to invasion of the lane in an overtaking maneuver, and 11.11\% for lost control of the vehicle. This research determines the areas with the highest accident rates along the Cuenca - Loja Road based on the physical characteristics of the road and the driving style. Fort the data acquisition a data logger device connected to the OBD II port was used that stores information such as speed, acceleration, and GPS, among others. Then, using automatic learning tools, the correlation between the different characteristics of the road (long slopes, road curves, etc.) and the driving style was determined in order to establish driving parameters appropriate to the geography and road surface.",

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Rivera Campoverde, N , Molina Campoverde, P & Molina Campoverde, J 2023, Estimation of Areas with the Highest Accident Rate on the Cuenca-Loja Road According to the Driving Maneuvers. in V Robles-Bykbaev, J Mula & G Reynoso-Meza (eds), Intelligent Technologies: Design and Applications for Society - Proceedings of CITIS 2022. Lecture Notes in Networks and Systems, vol. 607 LNNS, Springer Science and Business Media Deutschland GmbH, pp. 335-345, 8th International Conference on Science, Technology and Innovation for Society, CITIS 2022, Guayaquil, Ecuador, 22/06/22. https://doi.org/10.1007/978-3-031-24327-1_29

Estimation of Areas with the Highest Accident Rate on the Cuenca-Loja Road According to the Driving Maneuvers. / Rivera Campoverde, Néstor ; Molina Campoverde, Paúl; Molina Campoverde, Juan.
Intelligent Technologies: Design and Applications for Society - Proceedings of CITIS 2022. ed. / Vladimir Robles-Bykbaev; Josefa Mula; Gilberto Reynoso-Meza. Springer Science and Business Media Deutschland GmbH, 2023. p. 335-345 (Lecture Notes in Networks and Systems; Vol. 607 LNNS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Estimation of Areas with the Highest Accident Rate on the Cuenca-Loja Road According to the Driving Maneuvers

AU - Rivera Campoverde, Néstor

AU - Molina Campoverde, Paúl

AU - Molina Campoverde, Juan

PY - 2023

Y1 - 2023

N2 - Cuenca-Loja Road is a great reflection of the national reality, in the last five years, there have been 13 accidents of public transport vehicles, which left as consequences 159 injuries and 18 deaths. According to data from the National Traffic Agency (ANT) the main cause of accidents is the driver inexperience being 65.56% due to speeding, 23.33% due to invasion of the lane in an overtaking maneuver, and 11.11% for lost control of the vehicle. This research determines the areas with the highest accident rates along the Cuenca - Loja Road based on the physical characteristics of the road and the driving style. Fort the data acquisition a data logger device connected to the OBD II port was used that stores information such as speed, acceleration, and GPS, among others. Then, using automatic learning tools, the correlation between the different characteristics of the road (long slopes, road curves, etc.) and the driving style was determined in order to establish driving parameters appropriate to the geography and road surface.

AB - Cuenca-Loja Road is a great reflection of the national reality, in the last five years, there have been 13 accidents of public transport vehicles, which left as consequences 159 injuries and 18 deaths. According to data from the National Traffic Agency (ANT) the main cause of accidents is the driver inexperience being 65.56% due to speeding, 23.33% due to invasion of the lane in an overtaking maneuver, and 11.11% for lost control of the vehicle. This research determines the areas with the highest accident rates along the Cuenca - Loja Road based on the physical characteristics of the road and the driving style. Fort the data acquisition a data logger device connected to the OBD II port was used that stores information such as speed, acceleration, and GPS, among others. Then, using automatic learning tools, the correlation between the different characteristics of the road (long slopes, road curves, etc.) and the driving style was determined in order to establish driving parameters appropriate to the geography and road surface.

KW - Driving behavior

KW - Driving style

KW - Machine learning

KW - Traffic accidents

UR - https://www.scopus.com/pages/publications/85151046984

U2 - 10.1007/978-3-031-24327-1_29

DO - 10.1007/978-3-031-24327-1_29

M3 - Conference contribution

AN - SCOPUS:85151046984

SN - 9783031243264

T3 - Lecture Notes in Networks and Systems

SP - 335

EP - 345

BT - Intelligent Technologies

A2 - Robles-Bykbaev, Vladimir

A2 - Mula, Josefa

A2 - Reynoso-Meza, Gilberto

PB - Springer Science and Business Media Deutschland GmbH

T2 - 8th International Conference on Science, Technology and Innovation for Society, CITIS 2022

Y2 - 22 June 2022 through 24 June 2022

ER -

Rivera Campoverde N , Molina Campoverde P, Molina Campoverde J. Estimation of Areas with the Highest Accident Rate on the Cuenca-Loja Road According to the Driving Maneuvers. In Robles-Bykbaev V, Mula J, Reynoso-Meza G, editors, Intelligent Technologies: Design and Applications for Society - Proceedings of CITIS 2022. Springer Science and Business Media Deutschland GmbH. 2023. p. 335-345. (Lecture Notes in Networks and Systems). doi: 10.1007/978-3-031-24327-1_29

Estimation of Areas with the Highest Accident Rate on the Cuenca-Loja Road According to the Driving Maneuvers

Abstract

Publication series

Conference

Bibliographical note

UN SDGs

Keywords

CACES Knowledge Areas

Access to Document

Other files and links

Characterization of the vehicle fleet through the application of Machine Learning architectures to determine the effects on the society of the Cuenca canton

Cite this

Estimation of Areas with the Highest Accident Rate on the Cuenca-Loja Road According to the Driving Maneuvers

Abstract

Publication series

Conference

Bibliographical note

UN SDGs

Keywords

CACES Knowledge Areas

Access to Document

Other files and links

Projects

Characterization of the vehicle fleet through the application of Machine Learning architectures to determine the effects on the society of the Cuenca canton

Cite this