Vulnerable Road User Detection for Roadside-Assisted Safety Protection: A Comprehensive Survey
In recent years, the safety of vulnerable road users (VRUs), such as pedestrians, cyclists, and micro-mobility users, has become an increasingly significant concern in urban transportation systems worldwide. Reliable and accurate detection of VRUs is essential for effective safety protection. This s...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-03-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/15/7/3797 |
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| author | Ziyan Zhang Chuheng Wei Guoyuan Wu Matthew J. Barth |
| author_facet | Ziyan Zhang Chuheng Wei Guoyuan Wu Matthew J. Barth |
| author_sort | Ziyan Zhang |
| collection | DOAJ |
| description | In recent years, the safety of vulnerable road users (VRUs), such as pedestrians, cyclists, and micro-mobility users, has become an increasingly significant concern in urban transportation systems worldwide. Reliable and accurate detection of VRUs is essential for effective safety protection. This survey explores the techniques and methodologies used to detect VRUs, ranging from conventional methods to state-of-the-art (SOTA) approaches, with a primary focus on infrastructure-based detection. This study synthesizes findings from recent research papers and technical reports, emphasizing sensor modalities such as cameras, LiDAR, and RADAR. Furthermore, the survey examines benchmark datasets used to train and evaluate VRU detection models. Alongside innovative detection models and sufficient datasets, key challenges and emerging trends in algorithm development and dataset collection are also discussed. This comprehensive overview aims to provide insights into current advancements and inform the development of robust and reliable roadside detection systems to enhance the safety and efficiency of VRUs in modern transportation systems. |
| format | Article |
| id | doaj-art-a69376dcc3534a17a8dcf00c5f94bbf2 |
| institution | DOAJ |
| issn | 2076-3417 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-a69376dcc3534a17a8dcf00c5f94bbf22025-08-20T03:06:32ZengMDPI AGApplied Sciences2076-34172025-03-01157379710.3390/app15073797Vulnerable Road User Detection for Roadside-Assisted Safety Protection: A Comprehensive SurveyZiyan Zhang0Chuheng Wei1Guoyuan Wu2Matthew J. Barth3Center for Environmental Research and Technology (CE-CERT), Bourns College of Engineering, University of California, Riverside, CA 92507, USACenter for Environmental Research and Technology (CE-CERT), Bourns College of Engineering, University of California, Riverside, CA 92507, USACenter for Environmental Research and Technology (CE-CERT), Bourns College of Engineering, University of California, Riverside, CA 92507, USACenter for Environmental Research and Technology (CE-CERT), Bourns College of Engineering, University of California, Riverside, CA 92507, USAIn recent years, the safety of vulnerable road users (VRUs), such as pedestrians, cyclists, and micro-mobility users, has become an increasingly significant concern in urban transportation systems worldwide. Reliable and accurate detection of VRUs is essential for effective safety protection. This survey explores the techniques and methodologies used to detect VRUs, ranging from conventional methods to state-of-the-art (SOTA) approaches, with a primary focus on infrastructure-based detection. This study synthesizes findings from recent research papers and technical reports, emphasizing sensor modalities such as cameras, LiDAR, and RADAR. Furthermore, the survey examines benchmark datasets used to train and evaluate VRU detection models. Alongside innovative detection models and sufficient datasets, key challenges and emerging trends in algorithm development and dataset collection are also discussed. This comprehensive overview aims to provide insights into current advancements and inform the development of robust and reliable roadside detection systems to enhance the safety and efficiency of VRUs in modern transportation systems.https://www.mdpi.com/2076-3417/15/7/3797vulnerable road users (VRUs)object detectionsafetyintelligent transportation system (ITS) |
| spellingShingle | Ziyan Zhang Chuheng Wei Guoyuan Wu Matthew J. Barth Vulnerable Road User Detection for Roadside-Assisted Safety Protection: A Comprehensive Survey Applied Sciences vulnerable road users (VRUs) object detection safety intelligent transportation system (ITS) |
| title | Vulnerable Road User Detection for Roadside-Assisted Safety Protection: A Comprehensive Survey |
| title_full | Vulnerable Road User Detection for Roadside-Assisted Safety Protection: A Comprehensive Survey |
| title_fullStr | Vulnerable Road User Detection for Roadside-Assisted Safety Protection: A Comprehensive Survey |
| title_full_unstemmed | Vulnerable Road User Detection for Roadside-Assisted Safety Protection: A Comprehensive Survey |
| title_short | Vulnerable Road User Detection for Roadside-Assisted Safety Protection: A Comprehensive Survey |
| title_sort | vulnerable road user detection for roadside assisted safety protection a comprehensive survey |
| topic | vulnerable road users (VRUs) object detection safety intelligent transportation system (ITS) |
| url | https://www.mdpi.com/2076-3417/15/7/3797 |
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