基于深度神经网络的道路施工检测用于自动驾驶 / Deep Neural Network Based Roadwork Detection for Autonomous Driving
1️⃣ 一句话总结
这篇论文开发了一个结合YOLO神经网络和激光雷达数据的实时系统，能够准确检测和定位动态复杂的道路施工现场，为自动驾驶车辆提供更安全的导航支持。
arXiv 提交日期: 2026-04-02
Abstract - Deep Neural Network Based Roadwork Detection for Autonomous Driving
Road construction sites create major challenges for both autonomous vehicles and human drivers due to their highly dynamic and heterogeneous nature. This paper presents a real-time system that detects and localizes roadworks by combining a YOLO neural network with LiDAR data. The system identifies individual roadwork objects while driving, merges them into coherent construction sites and records their outlines in world coordinates. The model training was based on an adapted US dataset and a new dataset collected from test drives with a prototype vehicle in Berlin, Germany. Evaluations on real-world road construction sites showed a localization accuracy below 0.5 m. The system can support traffic authorities with up-to-date roadwork data and could enable autonomous vehicles to navigate construction sites more safely in the future.
源自 arXiv: 2604.02282