Why Studying Cut-ins? Comparing Cut-ins and Other Lane Changes Based on Naturalistic Driving Data

Yun Lu*, Dejiang Zheng, Rong Su, Avalpreet Singh Brar, Niels De Boer, Yong Liang Guan

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Extensive research has been conducted to explore vehicle lane changes, while the study on cut-ins has not received sufficient attention. The existing studies have not addressed the fundamental question of why studying cut-ins is crucial, despite the extensive investigation into lane changes. To tackle this issue, it is important to demonstrate how cut-ins, as a special type of lane change, differ from other lane changes. In this paper, we explore to compare driving characteristics of cut-ins and other lane changes based on naturalistic driving data. The highD dataset is employed to conduct the comparison. We extract all lane-change events from the dataset and exclude events that are not suitable for our comparison. Lane-change events are then categorized into the cut-in events and other lane-change events based on various gap-based rules. Several performance metrics are designed to measure the driving characteristics of the two types of events. We prove the significant differences between the cut-in behavior and other lane-change behavior by using the Wilcoxon rank-sum test. The results suggest the necessity of conducting specialized studies on cut-ins, offering valuable insights for future research in this field.

Original languageEnglish
Title of host publication35th IEEE Intelligent Vehicles Symposium, IV 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1135-1140
Number of pages6
ISBN (Electronic)9798350348811
DOIs
Publication statusPublished - 2024
Externally publishedYes
Event35th IEEE Intelligent Vehicles Symposium, IV 2024 - Jeju Island, Korea, Republic of
Duration: Jun 2 2024Jun 5 2024

Publication series

NameIEEE Intelligent Vehicles Symposium, Proceedings
ISSN (Print)1931-0587
ISSN (Electronic)2642-7214

Conference

Conference35th IEEE Intelligent Vehicles Symposium, IV 2024
Country/TerritoryKorea, Republic of
CityJeju Island
Period6/2/246/5/24

Bibliographical note

Publisher Copyright:
© 2024 IEEE.

ASJC Scopus Subject Areas

  • Computer Science Applications
  • Automotive Engineering
  • Modelling and Simulation

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