A Traffic Event Detection Method Based on Random Forest and Permutation Importance

Ziyi Su, Qingchao Liu, Chunxia Zhao and Fengming Sun
Additional contact information
Ziyi Su: School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210019, China
Qingchao Liu: Automotive Engineering Research Institute, Jiangsu University, Zhenjiang 212013, China
Chunxia Zhao: School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210019, China
Fengming Sun: School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210019, China

Mathematics, 2022, vol. 10, issue 6, 1-14

Abstract: Although the video surveillance system plays an important role in intelligent transportation, the limited camera views make it difficult to observe many traffic events. In this paper, we collect and combine the traffic flow variables from the multi-source sensors, and propose a PITED method based on Random Forest (RF) and Permutation importance (PI) for traffic event detection. This model selects the suitable traffic flow variables by means of permutation arrangement of importance, and establishes the whole process of acquisition, preprocessing, quantization, modeling and evaluation. Moreover, the real traffic data are collected and tested in this paper for evaluating the experiment performance, including the miss/false rate of traffic event, and average detection time. The experimental results show that the detection rate is more than 85% and the false alarm rate is less than 3%. It means the model is effective and efficient in the practical application regardless of both workdays and holidays.

Keywords: traffic event detection; variable selection method; improved random forest (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-7390/10/6/873/pdf (application/pdf)
https://www.mdpi.com/2227-7390/10/6/873/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:10:y:2022:i:6:p:873-:d:767572

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().