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 language | English |
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Title of host publication | 35th IEEE Intelligent Vehicles Symposium, IV 2024 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 1135-1140 |
Number of pages | 6 |
ISBN (Electronic) | 9798350348811 |
DOIs | |
Publication status | Published - 2024 |
Externally published | Yes |
Event | 35th IEEE Intelligent Vehicles Symposium, IV 2024 - Jeju Island, Korea, Republic of Duration: Jun 2 2024 → Jun 5 2024 |
Publication series
Name | IEEE Intelligent Vehicles Symposium, Proceedings |
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ISSN (Print) | 1931-0587 |
ISSN (Electronic) | 2642-7214 |
Conference
Conference | 35th IEEE Intelligent Vehicles Symposium, IV 2024 |
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Country/Territory | Korea, Republic of |
City | Jeju Island |
Period | 6/2/24 → 6/5/24 |
Bibliographical note
Publisher Copyright:© 2024 IEEE.
ASJC Scopus Subject Areas
- Computer Science Applications
- Automotive Engineering
- Modelling and Simulation