HAAR Characteristics-Based Traffic Volume Method Measurement for Street Intersections

Pattern Recognition Applications in EngineeringAdvances in Computer and Electrical Engineering(2020)

引用 0|浏览0
暂无评分
摘要
Traffic volume is an important measurement to design mobility strategies in cities such as traffic light configuration, civil engineering works, and others. This variable can be determined through different manual and automatic strategies. However, some street intersections, such as traffic circles, are difficult to determine their traffic volume and origin-destination matrices. In the case of manual strategies, it is difficult to count every single car in a mid to large-size traffic circle. On the other hand, automatic strategies can be difficult to develop because it is necessary to detect, track, and count vehicles that change position inside an intersection. This chapter presents a vehicle counting method to determine traffic volume and origin-destination matrix for traffic circle intersections using two main algorithms, Viola-Jones for detection and on-line boosting for tracking. The method is validated with an implementation applied to a top view video of a large-size traffic circle. The video is processed manually, and a comparison is presented.
更多
查看译文
关键词
traffic volume method measurement,haar,characteristics-based
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要