A review on the estimation of vulnerable road user behavior for automated vehicles.
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| Title: | A review on the estimation of vulnerable road user behavior for automated vehicles. |
|---|---|
| Authors: | Ara, Jinat1 (AUTHOR), Khan, Mohammad Badhruddouza2 (AUTHOR), Yasmin, Shamsunnahar3 (AUTHOR), Bhuiyan, Hanif4 (AUTHOR) hanifbhuiyan.c@gmail.com |
| Source: | International Journal of Sustainable Transportation. 2025, Vol. 19 Issue 6, p547-575. 29p. |
| Subjects: | Autonomous vehicles, Road users, Behavioral assessment, Research questions, Popularity |
| Abstract: | In recent years, the development of automated support systems for vehicles, focusing on enhancing digital traffic facilities through new methods and techniques has gained immense popularity. However, in real-life scenarios, the developed automated support systems are not completely compatible in terms of ensuring safety, effectiveness, and reliability. A promising number of research have emphasized the importance of integrating vulnerable road users' (VRUs) behavioral aspects into automated vehicle systems which might help to improve safety, effectiveness, reliability, and community acceptance. Addressing this research focus, this paper presents a comprehensive review focusing on VRU behavior analysis for automated vehicles, specifically examining studies related to VRUs' behavior aspects. We reviewed 73 studies addressing one research question: What aspects of automated vehicles need attention to improve their safety for VRUs? This review highlights and represents the findings focusing on three major groups: (I) VRUs crossing intention prediction, (II) VRUs motion prediction, and (III) VRUs path/trajectory prediction, concentrating on ten key aspects: (i) Improvement of VRUs context understanding, (ii) Early phase detection and prediction, (iii) Computational/Processing time, (iv) Consistent/Continuous prediction, (v) Interactive navigation, (vi) Semanticity, (vii) Low-scale dataset, (viii) Long-term prediction, (ix) Real-time prediction, and (x) Explainability improvement. Besides, it also addresses several challenges, such as difficulties in observing multiple scenarios, understanding contextual information, and detecting group behavior, which is crucial for enhancing the reliability and acceptability of automated vehicles in future research. The findings of this review are significant to provide new insights and directions for developing driving support systems for automated vehicles by integrating VRUs behavior. [ABSTRACT FROM AUTHOR] |
| Copyright of International Journal of Sustainable Transportation is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 185908026 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: A review on the estimation of vulnerable road user behavior for automated vehicles. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Ara%2C+Jinat%22">Ara, Jinat</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Khan%2C+Mohammad+Badhruddouza%22">Khan, Mohammad Badhruddouza</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Yasmin%2C+Shamsunnahar%22">Yasmin, Shamsunnahar</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Bhuiyan%2C+Hanif%22">Bhuiyan, Hanif</searchLink><relatesTo>4</relatesTo> (AUTHOR)<i> hanifbhuiyan.c@gmail.com</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Sustainable+Transportation%22">International Journal of Sustainable Transportation</searchLink>. 2025, Vol. 19 Issue 6, p547-575. 29p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Autonomous+vehicles%22">Autonomous vehicles</searchLink><br /><searchLink fieldCode="DE" term="%22Road+users%22">Road users</searchLink><br /><searchLink fieldCode="DE" term="%22Behavioral+assessment%22">Behavioral assessment</searchLink><br /><searchLink fieldCode="DE" term="%22Research+questions%22">Research questions</searchLink><br /><searchLink fieldCode="DE" term="%22Popularity%22">Popularity</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: In recent years, the development of automated support systems for vehicles, focusing on enhancing digital traffic facilities through new methods and techniques has gained immense popularity. However, in real-life scenarios, the developed automated support systems are not completely compatible in terms of ensuring safety, effectiveness, and reliability. A promising number of research have emphasized the importance of integrating vulnerable road users' (VRUs) behavioral aspects into automated vehicle systems which might help to improve safety, effectiveness, reliability, and community acceptance. Addressing this research focus, this paper presents a comprehensive review focusing on VRU behavior analysis for automated vehicles, specifically examining studies related to VRUs' behavior aspects. We reviewed 73 studies addressing one research question: What aspects of automated vehicles need attention to improve their safety for VRUs? This review highlights and represents the findings focusing on three major groups: (I) VRUs crossing intention prediction, (II) VRUs motion prediction, and (III) VRUs path/trajectory prediction, concentrating on ten key aspects: (i) Improvement of VRUs context understanding, (ii) Early phase detection and prediction, (iii) Computational/Processing time, (iv) Consistent/Continuous prediction, (v) Interactive navigation, (vi) Semanticity, (vii) Low-scale dataset, (viii) Long-term prediction, (ix) Real-time prediction, and (x) Explainability improvement. Besides, it also addresses several challenges, such as difficulties in observing multiple scenarios, understanding contextual information, and detecting group behavior, which is crucial for enhancing the reliability and acceptability of automated vehicles in future research. The findings of this review are significant to provide new insights and directions for developing driving support systems for automated vehicles by integrating VRUs behavior. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of International Journal of Sustainable Transportation is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1080/15568318.2025.2510413 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 29 StartPage: 547 Subjects: – SubjectFull: Autonomous vehicles Type: general – SubjectFull: Road users Type: general – SubjectFull: Behavioral assessment Type: general – SubjectFull: Research questions Type: general – SubjectFull: Popularity Type: general Titles: – TitleFull: A review on the estimation of vulnerable road user behavior for automated vehicles. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Ara, Jinat – PersonEntity: Name: NameFull: Khan, Mohammad Badhruddouza – PersonEntity: Name: NameFull: Yasmin, Shamsunnahar – PersonEntity: Name: NameFull: Bhuiyan, Hanif IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 06 Text: 2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 15568318 Numbering: – Type: volume Value: 19 – Type: issue Value: 6 Titles: – TitleFull: International Journal of Sustainable Transportation Type: main |
| ResultId | 1 |
