Estimating Traffic Flow By Image Processing and its Appliction to Fuzzy Adaptive Traffic Signal Control at an Isolated Intersection

碩士 === 國立交通大學 === 電機與控制工程系所 === 95 === Traffic information detection and adaptive traffic signal control are vital to the development of intelligent transportation system. The cycle length of a traffic signal controller can be adjusted dynamically by applying gathered traffic information to adaptive...

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Main Authors: Chi-De Lin, 林其德
Other Authors: Sheng-Fuu Lin
Format: Others
Language:zh-TW
Published: 2006
Online Access:http://ndltd.ncl.edu.tw/handle/61916173254783664345
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spelling ndltd-TW-095NCTU55910122016-05-27T04:18:38Z http://ndltd.ncl.edu.tw/handle/61916173254783664345 Estimating Traffic Flow By Image Processing and its Appliction to Fuzzy Adaptive Traffic Signal Control at an Isolated Intersection 以影像處理估測交通流量及其應用於獨立路口的模糊適應性交通號誌管理之研究 Chi-De Lin 林其德 碩士 國立交通大學 電機與控制工程系所 95 Traffic information detection and adaptive traffic signal control are vital to the development of intelligent transportation system. The cycle length of a traffic signal controller can be adjusted dynamically by applying gathered traffic information to adaptive traffic signal control at the isolated intersection, thus the traffic jams can be reduced. Detecting traffic information by use of image processing has become a trend, however, most of the previous research use microscopic measurement, which is unnecessary in application to adaptive traffic signal control. For adaptive traffic signal control system, the topic of optimal cycle is rarely considered since it has various lengths in each cycle; therefore, a very phase could have an overlong phase time. In view of this, an efficient image processing algorithm is proposed to estimate traffic flow in this thesis. In addition, an adaptive traffic signal control system that takes optimal cycle into account is presented. The contributions of this thesis may be summarized as follows. First, the relation of the number of foreground pixels and the number of foreground objects can be obtained by using perspective transformation. With the pre-constructed ellipse human template, the number of pedestrian on a crosswalk can be estimated approximately. Second, use the method mention above together with texture analysis of an image, the traffic flow can be normalized and represented by a number between 0 and 1. Third, a fuzzy adaptive traffic controller based on fuzzy inference system is proposed. The design of the system also takes optimal cycle and relative saturation degree of different roads into consideration. The image processing algorithm and fuzzy traffic signal controller have been tested in various situations; the system shows promise and the experiment results are satisfactory. Sheng-Fuu Lin 林昇甫 2006 學位論文 ; thesis 117 zh-TW
collection NDLTD
language zh-TW
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description 碩士 === 國立交通大學 === 電機與控制工程系所 === 95 === Traffic information detection and adaptive traffic signal control are vital to the development of intelligent transportation system. The cycle length of a traffic signal controller can be adjusted dynamically by applying gathered traffic information to adaptive traffic signal control at the isolated intersection, thus the traffic jams can be reduced. Detecting traffic information by use of image processing has become a trend, however, most of the previous research use microscopic measurement, which is unnecessary in application to adaptive traffic signal control. For adaptive traffic signal control system, the topic of optimal cycle is rarely considered since it has various lengths in each cycle; therefore, a very phase could have an overlong phase time. In view of this, an efficient image processing algorithm is proposed to estimate traffic flow in this thesis. In addition, an adaptive traffic signal control system that takes optimal cycle into account is presented. The contributions of this thesis may be summarized as follows. First, the relation of the number of foreground pixels and the number of foreground objects can be obtained by using perspective transformation. With the pre-constructed ellipse human template, the number of pedestrian on a crosswalk can be estimated approximately. Second, use the method mention above together with texture analysis of an image, the traffic flow can be normalized and represented by a number between 0 and 1. Third, a fuzzy adaptive traffic controller based on fuzzy inference system is proposed. The design of the system also takes optimal cycle and relative saturation degree of different roads into consideration. The image processing algorithm and fuzzy traffic signal controller have been tested in various situations; the system shows promise and the experiment results are satisfactory.
author2 Sheng-Fuu Lin
author_facet Sheng-Fuu Lin
Chi-De Lin
林其德
author Chi-De Lin
林其德
spellingShingle Chi-De Lin
林其德
Estimating Traffic Flow By Image Processing and its Appliction to Fuzzy Adaptive Traffic Signal Control at an Isolated Intersection
author_sort Chi-De Lin
title Estimating Traffic Flow By Image Processing and its Appliction to Fuzzy Adaptive Traffic Signal Control at an Isolated Intersection
title_short Estimating Traffic Flow By Image Processing and its Appliction to Fuzzy Adaptive Traffic Signal Control at an Isolated Intersection
title_full Estimating Traffic Flow By Image Processing and its Appliction to Fuzzy Adaptive Traffic Signal Control at an Isolated Intersection
title_fullStr Estimating Traffic Flow By Image Processing and its Appliction to Fuzzy Adaptive Traffic Signal Control at an Isolated Intersection
title_full_unstemmed Estimating Traffic Flow By Image Processing and its Appliction to Fuzzy Adaptive Traffic Signal Control at an Isolated Intersection
title_sort estimating traffic flow by image processing and its appliction to fuzzy adaptive traffic signal control at an isolated intersection
publishDate 2006
url http://ndltd.ncl.edu.tw/handle/61916173254783664345
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