Daniel Ulied, J. M. Parella, Estela Carmona Cejudo
{"title":"演示:集成V2X通信和计算机视觉的vru防撞系统","authors":"Daniel Ulied, J. M. Parella, Estela Carmona Cejudo","doi":"10.1109/VNC57357.2023.10136350","DOIUrl":null,"url":null,"abstract":"By enabling novel road safety use cases, vehicle-to-everything (V2X) technologies have the potential to contribute to reducing the number of accidents of vulnerable road users (VRU). However, most available road safety solutions rely on VRUs being equipped with on-board units (OBUs), thus hindering the uptake of V2X-based road safety solutions. In this demo, a collision avoidance system based on a hybrid approach is presented that does not rely on OBUs, thus reducing adoption costs. The system utilizes a tailor-made computer vision model, which is specifically designed to detect cyclists. This model is based on YOLOv5 and has the capability to detect cyclists as a single entity. V2X communication capabilities are based on the European Telecommunication Standards Institute (ETSI) Intelligent Transport Systems (ITS) standard. The demo showcases the system by presenting a realistic simulation incorporating the collision avoidance system.","PeriodicalId":185840,"journal":{"name":"2023 IEEE Vehicular Networking Conference (VNC)","volume":"649 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Demo: A Collision Avoidance System Integrating V2X Communication and Computer Vision for VRUs\",\"authors\":\"Daniel Ulied, J. M. Parella, Estela Carmona Cejudo\",\"doi\":\"10.1109/VNC57357.2023.10136350\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"By enabling novel road safety use cases, vehicle-to-everything (V2X) technologies have the potential to contribute to reducing the number of accidents of vulnerable road users (VRU). However, most available road safety solutions rely on VRUs being equipped with on-board units (OBUs), thus hindering the uptake of V2X-based road safety solutions. In this demo, a collision avoidance system based on a hybrid approach is presented that does not rely on OBUs, thus reducing adoption costs. The system utilizes a tailor-made computer vision model, which is specifically designed to detect cyclists. This model is based on YOLOv5 and has the capability to detect cyclists as a single entity. V2X communication capabilities are based on the European Telecommunication Standards Institute (ETSI) Intelligent Transport Systems (ITS) standard. The demo showcases the system by presenting a realistic simulation incorporating the collision avoidance system.\",\"PeriodicalId\":185840,\"journal\":{\"name\":\"2023 IEEE Vehicular Networking Conference (VNC)\",\"volume\":\"649 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-04-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 IEEE Vehicular Networking Conference (VNC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/VNC57357.2023.10136350\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE Vehicular Networking Conference (VNC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VNC57357.2023.10136350","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Demo: A Collision Avoidance System Integrating V2X Communication and Computer Vision for VRUs
By enabling novel road safety use cases, vehicle-to-everything (V2X) technologies have the potential to contribute to reducing the number of accidents of vulnerable road users (VRU). However, most available road safety solutions rely on VRUs being equipped with on-board units (OBUs), thus hindering the uptake of V2X-based road safety solutions. In this demo, a collision avoidance system based on a hybrid approach is presented that does not rely on OBUs, thus reducing adoption costs. The system utilizes a tailor-made computer vision model, which is specifically designed to detect cyclists. This model is based on YOLOv5 and has the capability to detect cyclists as a single entity. V2X communication capabilities are based on the European Telecommunication Standards Institute (ETSI) Intelligent Transport Systems (ITS) standard. The demo showcases the system by presenting a realistic simulation incorporating the collision avoidance system.