标题: 适用于ETC多车道环境下的执法演算法
A Non-payment Vehicle Searching Algorithm for ETC Multi-Lane Free Flow Environment
作者: 林良睿
Linm, Liang-Rui
简荣宏
Jan, Rong-Hong
资讯科学与工程研究所
关键字: 电子收费;多车道自由流;双分图;electronic toll collection;multilange free flow;bipartite graph
公开日期: 2011
摘要: 在电子收费(Electronic toll collection, ETC)系统中,利用车上机(On-Board Unit, OBU)与路边节点(Roadside Unit, RSU)快速的资料交换,可降低收费处理时间,进而提升车流量。ETC系统由四个模组构成:自动车辆辨识模组、自动车辆分类模组、扣款模组、影像执法模组。其中影像执法模组将每张车牌影像透过自动化车牌辨识 (Automatic License Plate Recognition, ALPR) 产生牌照号码,再利用牌照号码与车辆扣款资料比对找出未缴费与交易未成功之车辆。然而大量的车牌辨识会造成ETC系统的瓶颈。此外牌照号码与车辆扣款资料比对之运算,多车道(Multi-Lane Free Flow, MLFF)比单车道(Single-Lane Free Flow, SLFF)来的复杂。在本篇论文中,我们提出一个适用于ETC多车道环境下之模组,将车牌影像资料和扣款资讯匹配关系转换成双分图(Bipartite Graph)。针对双分图提出演算法以找出未缴费与交易未成功之车辆。模拟的结果显示出,我们提出的演算法可大幅的降低影像辨识的次数并提高执法系统的成功率。
There are many benefits of electronic toll collection (ETC) system such as reducing toll paying time, increasing the capacity of toll station, decreasing fuel consumption, enhancing the convenience of traveler and so on. For a multi-lane free flow ETC system, how to find out the non-payment vehicles without recognizing all license plate images is an important research problem. In this thesis, we formulate the non-payment vehicle searching problem into a bipartite graph and propose an algorithm without recognizing all license plate images for solving it. Simulation results show that our algorithm can reduce the number of ALPR (Automatic License Plate Recognition) and increase success rate of enforcement.
URI: http://140.113.39.130/cdrfb3/record/nctu/#GT079855525
http://hdl.handle.net/11536/48260
显示于类别:Thesis


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