Study on Driver Behavior Pattern in Merging Area under Naturalistic Driving Conditions
To reduce the risk of traffic conflicts in merging area, driver’s behavior pattern was analyzed to provide a theoretical basis for traffic control and conflict risk warning. The unmanned aerial vehicle (UAV) was used to collect the videos in two different types of merging zones: freeway interchange...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2024-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2024/7766164 |
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| _version_ | 1832553130096590848 |
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| author | Yan Li Han Zhang Qi Wang Zijian Wang Xinpeng Yao |
| author_facet | Yan Li Han Zhang Qi Wang Zijian Wang Xinpeng Yao |
| author_sort | Yan Li |
| collection | DOAJ |
| description | To reduce the risk of traffic conflicts in merging area, driver’s behavior pattern was analyzed to provide a theoretical basis for traffic control and conflict risk warning. The unmanned aerial vehicle (UAV) was used to collect the videos in two different types of merging zones: freeway interchange and service area. A vehicle tracking detection model based on YOLOv5 (the fifth version of You Only Look Once) and Deep SORT was constructed to extract traffic flow, speed, vehicle type, and driving trajectory. Acceleration/deceleration distribution and vehicle lane-changing behavior were analyzed. The influence of different vehicle models on vehicle speed and lane-changing behavior was summarized. Based on this data, the mean and standard deviation of velocity, acceleration, and variable acceleration were selected as the characteristic variables for driving style clustering. To avoid redundant information between features, principal component dimensionality reduction was performed, and the dimensionality reduction data was used for K-means and K-means++ clustering to obtain three driving styles. The results show that there are obvious differences in the driving behaviors of vehicles in different types of merging areas, and the characteristics of different areas should be fully considered when conducting traffic conflict warnings. |
| format | Article |
| id | doaj-art-714a6e99872c420b93c723af92c6f61f |
| institution | Kabale University |
| issn | 2042-3195 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-714a6e99872c420b93c723af92c6f61f2025-02-03T05:55:20ZengWileyJournal of Advanced Transportation2042-31952024-01-01202410.1155/2024/7766164Study on Driver Behavior Pattern in Merging Area under Naturalistic Driving ConditionsYan Li0Han Zhang1Qi Wang2Zijian Wang3Xinpeng Yao4Shandong Hi-Speed Construction Management Group Co. Ltd.School of Qilu TransportationSchool of Qilu TransportationShandong Hi-Speed Construction Management Group Co. Ltd.Shandong Hi-Speed Construction Management Group Co. Ltd.To reduce the risk of traffic conflicts in merging area, driver’s behavior pattern was analyzed to provide a theoretical basis for traffic control and conflict risk warning. The unmanned aerial vehicle (UAV) was used to collect the videos in two different types of merging zones: freeway interchange and service area. A vehicle tracking detection model based on YOLOv5 (the fifth version of You Only Look Once) and Deep SORT was constructed to extract traffic flow, speed, vehicle type, and driving trajectory. Acceleration/deceleration distribution and vehicle lane-changing behavior were analyzed. The influence of different vehicle models on vehicle speed and lane-changing behavior was summarized. Based on this data, the mean and standard deviation of velocity, acceleration, and variable acceleration were selected as the characteristic variables for driving style clustering. To avoid redundant information between features, principal component dimensionality reduction was performed, and the dimensionality reduction data was used for K-means and K-means++ clustering to obtain three driving styles. The results show that there are obvious differences in the driving behaviors of vehicles in different types of merging areas, and the characteristics of different areas should be fully considered when conducting traffic conflict warnings.http://dx.doi.org/10.1155/2024/7766164 |
| spellingShingle | Yan Li Han Zhang Qi Wang Zijian Wang Xinpeng Yao Study on Driver Behavior Pattern in Merging Area under Naturalistic Driving Conditions Journal of Advanced Transportation |
| title | Study on Driver Behavior Pattern in Merging Area under Naturalistic Driving Conditions |
| title_full | Study on Driver Behavior Pattern in Merging Area under Naturalistic Driving Conditions |
| title_fullStr | Study on Driver Behavior Pattern in Merging Area under Naturalistic Driving Conditions |
| title_full_unstemmed | Study on Driver Behavior Pattern in Merging Area under Naturalistic Driving Conditions |
| title_short | Study on Driver Behavior Pattern in Merging Area under Naturalistic Driving Conditions |
| title_sort | study on driver behavior pattern in merging area under naturalistic driving conditions |
| url | http://dx.doi.org/10.1155/2024/7766164 |
| work_keys_str_mv | AT yanli studyondriverbehaviorpatterninmergingareaundernaturalisticdrivingconditions AT hanzhang studyondriverbehaviorpatterninmergingareaundernaturalisticdrivingconditions AT qiwang studyondriverbehaviorpatterninmergingareaundernaturalisticdrivingconditions AT zijianwang studyondriverbehaviorpatterninmergingareaundernaturalisticdrivingconditions AT xinpengyao studyondriverbehaviorpatterninmergingareaundernaturalisticdrivingconditions |