Why Studying Cut-ins? Comparing Cut-ins and Other Lane Changes Based on Naturalistic Driving Data
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arXiv
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| Autori principali: | , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866914782555144192 |
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| author | Lu, Yun Zheng, Dejiang Su, Rong Brar, Avalpreet Singh de Boer, Niels Guan, Yong Liang |
| author_facet | Lu, Yun Zheng, Dejiang Su, Rong Brar, Avalpreet Singh de Boer, Niels Guan, Yong Liang |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2402_08289 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Why Studying Cut-ins? Comparing Cut-ins and Other Lane Changes Based on Naturalistic Driving Data Lu, Yun Zheng, Dejiang Su, Rong Brar, Avalpreet Singh de Boer, Niels Guan, Yong Liang Systems and Control Signal Processing 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. |
| title | Why Studying Cut-ins? Comparing Cut-ins and Other Lane Changes Based on Naturalistic Driving Data |
| topic | Systems and Control Signal Processing |
| url | https://arxiv.org/abs/2402.08289 |