ECE-VDTDA:在雾天气中提供驾驶员辅助的强大且计算效率高的避免碰撞系统
Naeem Raza1,2, Muhammad Asif Habib3, Abdullah M Albarrak3
1Department of Computer Science, National University of Modern Languages, Islamabad, Faisalabad Campus, Faisalabad, Punjab, Pakistan.
PloS one
|February 12, 2026
概括
一个高效和成本效益的车辆检测和跟踪与驾驶员辅助 (ECE-VDTDA) 系统改进了先进的驾驶员辅助系统 (ADAS) 和避免碰撞系统 (CAS) 在雾中. 该系统使用优化的SimYOLO-V5s_WIOU算法进行强大的车辆检测和跟踪,提高安全性.
科学领域:
- 计算机视觉 计算机视觉
- 机器人技术 机器人技术 机器人技术
- 汽车工程 汽车工程
背景情况:
- 先进的驾驶员辅助系统 (ADAS) 和避免碰撞系统 (CAS) 对现代车辆至关重要,特别是对前后碰撞的警告.
- 在雾等恶劣天气条件下,ADAS和CAS的性能显著降低,造成安全风险.
研究的目的:
- 提出一个高效和成本效益的车辆检测和跟踪与驾驶员辅助 (ECE-VDTDA) 系统,以提高雾天气中的ADAS和CAS性能.
- 开发和评估一个优化的SimYOLO-V5s_WIOU车辆检测算法,并将其与先进的跟踪算法集成,以提高准确性和效率.
主要方法:
- 开发了一个优化的SimYOLO-V5s_WIOU车辆检测算法,结合了SimSPPF和智能交叉对联 (WIOU) 损失.
- 利用最先进的深度SORT,强度SORT和优化的深度SORT算法来追踪车辆.
- 集成检测和跟踪模块与驾驶员辅助模块进行实时碰撞警告.
主要成果:
- 与基线YOLO-V5s相比,SimYOLO-V5s_WIOU算法显示出显著的性能改进,包括在雾驾驶数据集上的mAP50增加了17.45%.
- 在雾的城市景观数据集上,在多类mAP50,mAP50-95,F1得分,精度和回忆方面取得了显著的增长.
- ECE-VDTDA系统实现了高可靠性的车辆跟踪,并在多个雾气天气数据集中展示了稳定性和计算效率.
结论:
- 拟议的ECE-VDTDA系统,由优化的SimYOLO-V5s_WIOU算法提供动力,有效地提高了车辆在雾条件下的检测和跟踪.
- 该系统的驾驶员辅助模块通过估计关键驾驶参数,提供及时的碰撞警告,从而提高道路安全.
- 实验结果验证了ECE-VDTDA系统在恶劣天气下用于自动驾驶应用的稳定性,计算效率和实用性.
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