CAJ | 학술논문

目前，高速公路交通拥堵日趋频繁，然而大部分高速公路的管理方式仍然是通过人工查看轮巡监控视频来发现交通拥堵，效率低下。本文提出一种对高速公路轮巡监控视频自动检测交通拥堵的方法。该方法实时检测监控视频场景是否轮巡、切换、变动，自适应提取变动场景的道路边界结构并分类，然后在提取的道路边界结构范围内，计算宏观边缘占有率与加权平均光流速度两个宏观交通状态参数，并构造特征集，根据不同的道路边界类型选择对应支持向量机来实现对交通拥堵的自动检测和判别。实验结果表明，该方法能有效地对轮巡模式工作的高速公路监控视频检测交通拥堵，检测时间不大于30s，检测正确率达91．8％。
목전，고속공로교통옹도일추빈번，연이대부분고속공로적관리방식잉연시통과인공사간륜순감공시빈래발현교통옹도，효솔저하。본문제출일충대고속공로륜순감공시빈자동검측교통옹도적방법。해방법실시검측감공시빈장경시부륜순、절환、변동，자괄응제취변동장경적도로변계결구병분류，연후재제취적도로변계결구범위내，계산굉관변연점유솔여가권평균광류속도량개굉관교통상태삼수，병구조특정집，근거불동적도로변계류형선택대응지지향량궤래실현대교통옹도적자동검측화판별。실험결과표명，해방법능유효지대륜순모식공작적고속공로감공시빈검측교통옹도，검측시간불대우30s，검측정학솔체91．8％。
Traffic congestion is increasingly serious in expressway , and manual surveillance is still a main way to find traffic con-gestion, which is very ineffective .In this paper, an automatic traffic congestion detection method for expressway surveillance vid-eos is presented .Firstly, the road boundary structure of surveillance video is extracted adaptively .Secondly , edge occupancy rate and weighted average velocity of optical flow in the range of extracted road are calculated .Finally, the traffic congestion is detec-ted by analyzing the two macro traffic state parameters .The experimental test results show that this method is effective for express-way switching surveillance video , the detection time is less than 30 seconds, and the detection accuracy rate is above 91.8%.