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  4. Compensation and Regulation for Vehicle Detector Data
 
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Compensation and Regulation for Vehicle Detector Data

Date Issued
2009
Date
2009
Author(s)
Huang, Hung-Jen
URI
http://ntur.lib.ntu.edu.tw//handle/246246/187864
Abstract
Collecting traffic data for advanced use in Intelligent Transportation Systems (ITS) heavily relies on the performance of vehicle detectors. The completeness and the accuracy of data measurement depend on the quality of vehicle detector and whether it is installed at appropriate position. Missing data and inaccuracy traffic parameters prevent Real-time Traffic Control Systems (RTCS) from continuous working and decrease control performance,. These disadvantages decrease the value of vehicle detector investment. This dissertation develops a novel compensation mechanism for missing data by integrating Central Limit Theorem, Fourier Transforms, Kalman Filter, and Genetic Algorithm. The interpolation considers the central tendency of historical data of large number and immediate past data in the current day. All experiment results show that the proposed compensation methods perform well under the Lewis (1989) criteria. In addition, the interpolation methods with Kalman Filter perform an accurate result when the missing rate is under 30% by fusing historical data and the immediate past data in the current day. Even though the employed vehicle detectors can work reliably and reply traffic data continuously, installation at improper positions shall make the measurement disturbed by the nearby traffic signal. This dissertation utilizes optimal control theory to dynamically track whether the position of vehicle detector is proper and to automatically regulate the noised data to be similar to those collected in a proper site. The results show that the difference between regulated and non-regulated speed data is up to 91.45%. The difference leads yellow and all-red intervals obtained by non-regulated data differ from those obtained by regulated ones to 54%. The test proves that the regulated speed and occupancy do not significantly differ from those not disturbed by traffic signals. The findings reveal that the regulation is needed for the system to obtain real traffic conditions without the noise from signal control and then to decide the adaptive yellow and all-red intervals, clearance, lost time, and timing plan. In summary, this dissertation proposes efficient methods to compensate missing data and regulate the data disturbed by traffic signal due to improper positions of vehicle detectors. The proposed methods will support RTCS to continuously obtain the data similar to those without the noise from traffic signal. The findings shall contribute to ITS.
Subjects
vehicle detector
missing data
data compensation
traffic control
signal timing plan
traffic data regulation
Type
thesis
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ntu-98-D92521008-1.pdf

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