用光纤传感检测车辆变道，提前发现单车道异常
Vehicle behaviour estimation for abnormal event detection using distributed fiber optic sensing
- 通过振动频谱中心变化追踪车辆路径与变道行为
- 真实交通数据验证，变道检测准确率达80%
- 适合智能交通系统异常监测，尤其适用于已有光缆路段
分布式光纤传感（DFOS）系统是一种利用现有光纤基础设施进行广域交通监控的低成本技术，可有效检测交通拥堵。然而，检测导致拥堵的单车道异常仍具挑战性。这些异常可通过监测车辆为避让拥堵而进行的变道行为来识别。本文提出一种方法，通过跟踪车辆轨迹并检测道路特定路段上的车辆变道行为，实现单车道异常检测。我们采用聚类技术估计车辆在所有时间点的位置，并拟合其行驶路径。通过持续追踪参考车辆的振动频谱中心变化，检测车辆变道行为。使用真实交通数据评估该方法，结果显示变道检测事件的准确率达到80%，表明其能有效识别异常存在。
原文摘要 · Abstract (English)
The distributed fiber-optic sensing (DFOS) system is a cost-effective wide-area traffic monitoring technology that utilizes existing fiber infrastructure to effectively detect traffic congestions. However, detecting single-lane abnormalities, that lead to congestions, is still a challenge. These single-lane abnormalities can be detected by monitoring lane change behaviour of vehicles, performed to avoid congestion along the monitoring section of a road. This paper presents a method to detect single-lane abnormalities by tracking individual vehicle paths and detecting vehicle lane changes along a section of a road. We propose a method to estimate the vehicle position at all time instances and fit a path using clustering techniques. We detect vehicle lane change by monitoring any change in spectral centroid of vehicle vibrations by tracking a reference vehicle along a highway. The evaluation of our proposed method with real traffic data showed 80% accuracy for lane change detection events that represent presence of abnormalities.
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