高载客量车辆车道执法系统

Q3 Social Sciences
Jinhwan Jang
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引用次数: 0

摘要

开发并评估了高载客车辆车道自动执法系统。警方目前的人工执法做法带来了安全问题和不必要的交通延误。在韩国,只有乘坐5人以上的车辆才能在高速公路上使用HOV专用车道。因此,检测hov的乘客数量是其发展的核心要素。为了快速检测乘客,建立了基于yolo的乘客检测模型。该系统包括三个红外摄像头:两个用于车厢探测,另一个用于车牌识别。此外,还采用了与摄像头和激光传感器相同频率的多路红外照明,用于车辆检测和测速。利用在试验场收集的真实数据对所开发系统的性能进行了评估。结果显示,乘客检测的平均错误率为9%。根据方差分析(ANOVA),这些表现显示车速和乘客数量没有差异。利用开发的系统,可以采取更有效和更安全的HOV车道执法措施。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
High-Occupancy Vehicle Lane Enforcement System
An automatic High-Occupancy Vehicle (HOV) lane enforcement system is developed and evaluated. Current manual enforcement practices by the police bring about safety concerns and unnecessary traffic delays. Only vehicles with more than five passengers are permitted to use HOV lanes on freeways in Korea. Hence, detecting the number of passengers in HOVs is a core element for their development. For a quick detection capability, a YOLO-based passenger detection model was built. The system comprises three infrared cameras: two are for compartment detection and the other is for number plate recognition. Multiple infrared illuminations with the same frequency as the cameras and laser sensors for vehicle detection and speed measurement are also employed. The performance of the developed system is evaluated with real-world data collected on proving ground. As a result, it showed a passenger detection error of nine percent on average. The performances revealed no difference in vehicle speeds and the number of passengers according to ANOVA tests. Using the developed system, more efficient and safer HOV lane enforcement practices can be made.
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来源期刊
Open Transportation Journal
Open Transportation Journal Social Sciences-Transportation
CiteScore
2.10
自引率
0.00%
发文量
19
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