Calculation of Driving Parameters for GOA4 Signaling System using Machine Learning Methods

Mehmet Taciddin Akçay; Abdurrahim Akgundogdu

doi:10.35377/saucis...932969

EN

Calculation of Driving Parameters for GOA4 Signaling System using Machine Learning Methods

Abstract

Among the electromechanical components of the rail system, the rail system vehicle is one of the most important units that carrying the passenger load. In terms of the efficiency of the signalization system, it is very critical to create the optimum vehicle driving profile. While many parameters of the vehicle come into play while designing the driving profile, determining the acceleration and braking accelerations directly affects this characteristic. With the developing technology in rail transportation systems, the use of programmable devices and software instead of human factors is becoming more widespread day by day. Among the software used, artificial intelligence and machine learning applications constitute a large share in the general distribution. Especially if driverless (GOA4) signaling systems are preferred, these software become more important. In this study, the estimation of Vehicle Acceleration and Braking Acceleration with travel time has been carried out by using Machine Learning Methods. The ideal results obtained were given comparatively and interpreted on the graphics.

Keywords

References

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Details

Primary Language

English

Subjects

Engineering

Journal Section

Research Article

Authors

Mehmet Taciddin Akçay ^*
0000-0002-1050-4566
Türkiye

Abdurrahim Akgundogdu
0000-0001-8113-0277
Türkiye

Publication Date

April 30, 2022

Submission Date

May 5, 2021

Acceptance Date

March 10, 2022

Published in Issue

Year 1970 Volume: 5 Number: 1

DOI

https://doi.org/10.35377/saucis...932969

IZ

https://izlik.org/JA28JL94FM

Cite

RIS / Bibtex

APA

Akçay, M. T., & Akgundogdu, A. (2022). Calculation of Driving Parameters for GOA4 Signaling System using Machine Learning Methods. Sakarya University Journal of Computer and Information Sciences, 5(1), 62-70. https://doi.org/10.35377/saucis...932969

AMA

1.Akçay MT, Akgundogdu A. Calculation of Driving Parameters for GOA4 Signaling System using Machine Learning Methods. SAUCIS. 2022;5(1):62-70. doi:10.35377/saucis.932969

Chicago

Akçay, Mehmet Taciddin, and Abdurrahim Akgundogdu. 2022. “Calculation of Driving Parameters for GOA4 Signaling System Using Machine Learning Methods”. Sakarya University Journal of Computer and Information Sciences 5 (1): 62-70. https://doi.org/10.35377/saucis. 932969.

EndNote

Akçay MT, Akgundogdu A (April 1, 2022) Calculation of Driving Parameters for GOA4 Signaling System using Machine Learning Methods. Sakarya University Journal of Computer and Information Sciences 5 1 62–70.

IEEE

[1]M. T. Akçay and A. Akgundogdu, “Calculation of Driving Parameters for GOA4 Signaling System using Machine Learning Methods”, SAUCIS, vol. 5, no. 1, pp. 62–70, Apr. 2022, doi: 10.35377/saucis...932969.

ISNAD

Akçay, Mehmet Taciddin - Akgundogdu, Abdurrahim. “Calculation of Driving Parameters for GOA4 Signaling System Using Machine Learning Methods”. Sakarya University Journal of Computer and Information Sciences 5/1 (April 1, 2022): 62-70. https://doi.org/10.35377/saucis. 932969.

JAMA

1.Akçay MT, Akgundogdu A. Calculation of Driving Parameters for GOA4 Signaling System using Machine Learning Methods. SAUCIS. 2022;5:62–70.

MLA

Akçay, Mehmet Taciddin, and Abdurrahim Akgundogdu. “Calculation of Driving Parameters for GOA4 Signaling System Using Machine Learning Methods”. Sakarya University Journal of Computer and Information Sciences, vol. 5, no. 1, Apr. 2022, pp. 62-70, doi:10.35377/saucis. 932969.

Vancouver

1.Mehmet Taciddin Akçay, Abdurrahim Akgundogdu. Calculation of Driving Parameters for GOA4 Signaling System using Machine Learning Methods. SAUCIS. 2022 Apr. 1;5(1):62-70. doi:10.35377/saucis. 932969