Prototype of Driving Behavior Monitoring System Using Naïve Bayes Classification Method

Eko Pramunanto; Ahmad Zaini; Vathya Rizkiana

doi:10.1109/CENIM48368.2019.8973232

Prototype of Driving Behavior Monitoring System Using Naïve Bayes Classification Method

Eko Pramunanto
, Ahmad Zaini
, Vathya Rizkiana

Institut Teknologi Sepuluh Nopember

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

2 Citations (Scopus)

Abstract

The transportation needs of the Indonesian people, especially for land routes, are increasing per year. According to Indonesia Central Bureau of Statistics, in 2016 the number of passenger cars in Indonesia was 14,580,666 units. This number rose 7.8% from the previous year. However, the accident rate in Indonesia is still relatively high. In 2017, the number of accidents in Indonesia was 98,400. One reason for the occurrence of traffic accidents is the lack of good driver behavior. In this study, a prototype system was proposed that can monitor the driving behavior of drivers of four-wheeled vehicles using Naïve Bayes Classification method. Using the event detection and feature extraction methods, this system will classify the categories of driver's driving behavior into three classes; defensive, normal, and aggressive. The results of the validation show that the accuracy of the method used is 86% for longitudinal events and 95.8% for lateral events.

Original language	English
Title of host publication	2019 International Conference on Computer Engineering, Network, and Intelligent Multimedia, CENIM 2019 - Proceeding
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781728129655
DOIs	https://doi.org/10.1109/CENIM48368.2019.8973232
Publication status	Published - Nov 2019
Event	2nd International Conference on Computer Engineering, Network, and Intelligent Multimedia, CENIM 2019 - Surabaya, Indonesia Duration: 19 Nov 2019 → 20 Nov 2019

Publication series

Name	2019 International Conference on Computer Engineering, Network, and Intelligent Multimedia, CENIM 2019 - Proceeding
Volume	2019-November

Conference

Conference	2nd International Conference on Computer Engineering, Network, and Intelligent Multimedia, CENIM 2019
Country/Territory	Indonesia
City	Surabaya
Period	19/11/19 → 20/11/19

UN SDGs

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

SDG 3 Good Health and Well-being

Keywords

Driving Behavior
Naïve Bayes
event detection

Access to Document

10.1109/CENIM48368.2019.8973232

Cite this

Pramunanto, E., Zaini, A., & Rizkiana, V. (2019). Prototype of Driving Behavior Monitoring System Using Naïve Bayes Classification Method. In 2019 International Conference on Computer Engineering, Network, and Intelligent Multimedia, CENIM 2019 - Proceeding Article 8973232 (2019 International Conference on Computer Engineering, Network, and Intelligent Multimedia, CENIM 2019 - Proceeding; Vol. 2019-November). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CENIM48368.2019.8973232

Pramunanto, Eko ; Zaini, Ahmad ; Rizkiana, Vathya. / Prototype of Driving Behavior Monitoring System Using Naïve Bayes Classification Method. 2019 International Conference on Computer Engineering, Network, and Intelligent Multimedia, CENIM 2019 - Proceeding. Institute of Electrical and Electronics Engineers Inc., 2019. (2019 International Conference on Computer Engineering, Network, and Intelligent Multimedia, CENIM 2019 - Proceeding).

@inproceedings{832064dbfb7142f19ecd24e49c4b1ceb,

title = "Prototype of Driving Behavior Monitoring System Using Na{\"i}ve Bayes Classification Method",

abstract = "The transportation needs of the Indonesian people, especially for land routes, are increasing per year. According to Indonesia Central Bureau of Statistics, in 2016 the number of passenger cars in Indonesia was 14,580,666 units. This number rose 7.8\% from the previous year. However, the accident rate in Indonesia is still relatively high. In 2017, the number of accidents in Indonesia was 98,400. One reason for the occurrence of traffic accidents is the lack of good driver behavior. In this study, a prototype system was proposed that can monitor the driving behavior of drivers of four-wheeled vehicles using Na{\"i}ve Bayes Classification method. Using the event detection and feature extraction methods, this system will classify the categories of driver's driving behavior into three classes; defensive, normal, and aggressive. The results of the validation show that the accuracy of the method used is 86\% for longitudinal events and 95.8\% for lateral events.",

keywords = "Driving Behavior, Na{\"i}ve Bayes, event detection",

author = "Eko Pramunanto and Ahmad Zaini and Vathya Rizkiana",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2nd International Conference on Computer Engineering, Network, and Intelligent Multimedia, CENIM 2019 ; Conference date: 19-11-2019 Through 20-11-2019",

year = "2019",

month = nov,

doi = "10.1109/CENIM48368.2019.8973232",

language = "English",

series = "2019 International Conference on Computer Engineering, Network, and Intelligent Multimedia, CENIM 2019 - Proceeding",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2019 International Conference on Computer Engineering, Network, and Intelligent Multimedia, CENIM 2019 - Proceeding",

address = "United States",

}

Pramunanto, E , Zaini, A & Rizkiana, V 2019, Prototype of Driving Behavior Monitoring System Using Naïve Bayes Classification Method. in 2019 International Conference on Computer Engineering, Network, and Intelligent Multimedia, CENIM 2019 - Proceeding., 8973232, 2019 International Conference on Computer Engineering, Network, and Intelligent Multimedia, CENIM 2019 - Proceeding, vol. 2019-November, Institute of Electrical and Electronics Engineers Inc., 2nd International Conference on Computer Engineering, Network, and Intelligent Multimedia, CENIM 2019, Surabaya, Indonesia, 19/11/19. https://doi.org/10.1109/CENIM48368.2019.8973232

Prototype of Driving Behavior Monitoring System Using Naïve Bayes Classification Method. / Pramunanto, Eko ; Zaini, Ahmad; Rizkiana, Vathya.
2019 International Conference on Computer Engineering, Network, and Intelligent Multimedia, CENIM 2019 - Proceeding. Institute of Electrical and Electronics Engineers Inc., 2019. 8973232 (2019 International Conference on Computer Engineering, Network, and Intelligent Multimedia, CENIM 2019 - Proceeding; Vol. 2019-November).

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

TY - GEN

T1 - Prototype of Driving Behavior Monitoring System Using Naïve Bayes Classification Method

AU - Pramunanto, Eko

AU - Zaini, Ahmad

AU - Rizkiana, Vathya

PY - 2019/11

Y1 - 2019/11

N2 - The transportation needs of the Indonesian people, especially for land routes, are increasing per year. According to Indonesia Central Bureau of Statistics, in 2016 the number of passenger cars in Indonesia was 14,580,666 units. This number rose 7.8% from the previous year. However, the accident rate in Indonesia is still relatively high. In 2017, the number of accidents in Indonesia was 98,400. One reason for the occurrence of traffic accidents is the lack of good driver behavior. In this study, a prototype system was proposed that can monitor the driving behavior of drivers of four-wheeled vehicles using Naïve Bayes Classification method. Using the event detection and feature extraction methods, this system will classify the categories of driver's driving behavior into three classes; defensive, normal, and aggressive. The results of the validation show that the accuracy of the method used is 86% for longitudinal events and 95.8% for lateral events.

AB - The transportation needs of the Indonesian people, especially for land routes, are increasing per year. According to Indonesia Central Bureau of Statistics, in 2016 the number of passenger cars in Indonesia was 14,580,666 units. This number rose 7.8% from the previous year. However, the accident rate in Indonesia is still relatively high. In 2017, the number of accidents in Indonesia was 98,400. One reason for the occurrence of traffic accidents is the lack of good driver behavior. In this study, a prototype system was proposed that can monitor the driving behavior of drivers of four-wheeled vehicles using Naïve Bayes Classification method. Using the event detection and feature extraction methods, this system will classify the categories of driver's driving behavior into three classes; defensive, normal, and aggressive. The results of the validation show that the accuracy of the method used is 86% for longitudinal events and 95.8% for lateral events.

KW - Driving Behavior

KW - Naïve Bayes

KW - event detection

UR - https://www.scopus.com/pages/publications/85084471076

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DO - 10.1109/CENIM48368.2019.8973232

M3 - Conference contribution

AN - SCOPUS:85084471076

T3 - 2019 International Conference on Computer Engineering, Network, and Intelligent Multimedia, CENIM 2019 - Proceeding

BT - 2019 International Conference on Computer Engineering, Network, and Intelligent Multimedia, CENIM 2019 - Proceeding

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2nd International Conference on Computer Engineering, Network, and Intelligent Multimedia, CENIM 2019

Y2 - 19 November 2019 through 20 November 2019

ER -

Pramunanto E , Zaini A, Rizkiana V. Prototype of Driving Behavior Monitoring System Using Naïve Bayes Classification Method. In 2019 International Conference on Computer Engineering, Network, and Intelligent Multimedia, CENIM 2019 - Proceeding. Institute of Electrical and Electronics Engineers Inc. 2019. 8973232. (2019 International Conference on Computer Engineering, Network, and Intelligent Multimedia, CENIM 2019 - Proceeding). doi: 10.1109/CENIM48368.2019.8973232

Prototype of Driving Behavior Monitoring System Using Naïve Bayes Classification Method

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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Cite this