Proceedings of the 2022 2nd International Conference on Education, Information Management and Service Science (EIMSS 2022)

<Previous Article In Volume
Next Article In Volume>

Recognition of Abnormal Driving Behavior of Highway Vehicles Based on Data Characteristics

Authors
Jiahao Feng1, Jinsong Ye2, *, Lei Zhou2
1Beijing Wuzi University, Beijing, China
2China Academy of Transportation Sciences, Beijing, China
*Corresponding author. Email: yejs@motcats.ac.cn
Corresponding Author
Jinsong Ye
Available Online 12 December 2022.
DOI
10.2991/978-94-6463-024-4_29How to use a DOI?
Keywords
highway; traffic big data; abnormal driving behavior; data identification characteristics; online calculation
Abstract

Using the data characteristics of traffic big data to intelligently identify abnormal driving vehicles, it is of great significance to fight against toll evasion and improve operation management & efficiency of highway. To improve the efficiency of joint inspection of existing highway vehicle toll evasion behaviors, this paper carries out behavioral analysis and data analysis on the five existing abnormal driving behaviors, and summarizes the data characteristics of five abnormal driving behaviors: breakthrough type, alternate use of OBU, vehicle type history issues, vehicle timeout and overspeed. According to data characteristics of each type, this paper presents an online calculation method of abnormal driving behavior based on data features of threshold table, sliding window. This paper concluded that the characteristics of vehicle data can effectively identify abnormal driving behaviors on highways and improve the efficiency of inspection.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

<Previous Article In Volume
Next Article In Volume>
Volume Title
Proceedings of the 2022 2nd International Conference on Education, Information Management and Service Science (EIMSS 2022)
Series
Atlantis Highlights in Computer Sciences
Publication Date
12 December 2022
ISBN
10.2991/978-94-6463-024-4_29
ISSN
2589-4900
DOI
10.2991/978-94-6463-024-4_29How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Jiahao Feng
AU  - Jinsong Ye
AU  - Lei Zhou
PY  - 2022
DA  - 2022/12/12
TI  - Recognition of Abnormal Driving Behavior of Highway Vehicles Based on Data Characteristics
BT  - Proceedings of the 2022 2nd International Conference on Education, Information Management and Service Science (EIMSS 2022)
PB  - Atlantis Press
SP  - 272
EP  - 284
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-024-4_29
DO  - 10.2991/978-94-6463-024-4_29
ID  - Feng2022
ER  -