Vehicle-in-Virtual-Environment (VVE) Method for Developing and Evaluating VRU Safety of Connected and Autonomous Driving with Focus on Bicyclist Safety
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866908511687933952 |
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| author | Chen, Haochong Cao, Xincheng Aksun-Guvenc, Bilin Guvenc, Levent |
| author_facet | Chen, Haochong Cao, Xincheng Aksun-Guvenc, Bilin Guvenc, Levent |
| contents | Extensive research has already been conducted in the autonomous driving field to help vehicles navigate safely and efficiently. At the same time, plenty of current research on vulnerable road user (VRU) safety is performed which largely concentrates on perception, localization, or trajectory prediction of VRUs. However, existing research still exhibits several gaps, including the lack of a unified planning and collision avoidance system for autonomous vehicles, limited investigation into delay tolerant control strategies, and the absence of an efficient and standardized testing methodology. Ensuring VRU safety remains one of the most pressing challenges in autonomous driving, particularly in dynamic and unpredictable environments. In this two year project, we focused on applying the Vehicle in Virtual Environment (VVE) method to develop, evaluate, and demonstrate safety functions for Vulnerable Road Users (VRUs) using automated steering and braking of ADS. In this current second year project report, our primary focus was on enhancing the previous year results while also considering bicyclist safety. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_00624 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Vehicle-in-Virtual-Environment (VVE) Method for Developing and Evaluating VRU Safety of Connected and Autonomous Driving with Focus on Bicyclist Safety Chen, Haochong Cao, Xincheng Aksun-Guvenc, Bilin Guvenc, Levent Robotics Systems and Control Extensive research has already been conducted in the autonomous driving field to help vehicles navigate safely and efficiently. At the same time, plenty of current research on vulnerable road user (VRU) safety is performed which largely concentrates on perception, localization, or trajectory prediction of VRUs. However, existing research still exhibits several gaps, including the lack of a unified planning and collision avoidance system for autonomous vehicles, limited investigation into delay tolerant control strategies, and the absence of an efficient and standardized testing methodology. Ensuring VRU safety remains one of the most pressing challenges in autonomous driving, particularly in dynamic and unpredictable environments. In this two year project, we focused on applying the Vehicle in Virtual Environment (VVE) method to develop, evaluate, and demonstrate safety functions for Vulnerable Road Users (VRUs) using automated steering and braking of ADS. In this current second year project report, our primary focus was on enhancing the previous year results while also considering bicyclist safety. |
| title | Vehicle-in-Virtual-Environment (VVE) Method for Developing and Evaluating VRU Safety of Connected and Autonomous Driving with Focus on Bicyclist Safety |
| topic | Robotics Systems and Control |
| url | https://arxiv.org/abs/2509.00624 |