Browsing by Author "Tseng, Ming-Te"

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A support vector machine approach to CMOS-based radar signal processing for vehicle classification and speed estimation
(2013-07-01)
Cho, Hsun-Jung
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Tseng, Ming-Te
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運輸與物流管理系註：原交通所+運管所
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Department of Transportation and Logistics Management
In this work, a complementary metal-oxide semiconductor (CMOS) based transceiver with a sensitivity time control antenna is successfully implemented for advanced traffic signal processing. The collected signals from the CMOS radar system are processed with optimization algorithms for vehicle-type classification and speed determination. The high recognition rate optimization algorithms are mainly based upon the information of short setup time and different environmental installation of each sensor. In the course of optimization, a video recognition module is further adopted as a supervisor of support vector machine and support vector regression. Compared with conventional circuit-based detector systems, the developed CMOS radar integrates submicron semiconductor devices and thus not only possesses low stand-by power but also is ready for production. In the meantime, the developed algorithm of this study simultaneously optimizes the vehicle-type classification and speed determination in a computationally cost-effective manner, which benefits real-time intelligent transportation systems. (C) 2013 Published by Elsevier Ltd
Method for identification of traffic lane boundary
(2010-06-24)
Jou, Yow-Jen
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Cho, Hsun-Jung
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Chen, Yu-Kuang
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Huang, Heng
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Hsu, Chia-Chun
The invention provides a method for identification of traffic lane boundary. Firstly the microwave signal is received, and the noise reduction is treated for the microwave signal. Then the frequency domain information is employed to calculate the legal set of closed interval, in order to form the frequency span information. Finally, the probability density function model is employed to calculate the frequency span information in order to identify the traffic lane boundary.
Shockwave detection for electronic vehicle detectors
(2007)
Cho, Hsung-Jung
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Tseng, Ming-Te
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運輸與物流管理系註：原交通所+運管所
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Department of Transportation and Logistics Management
Although shockwaves have been extensively adopted in traditional traffic flow theory, how to detect shockwaves using an electronic vehicle detector has Dot been explored. Therefore, this study illustrates, for the first time, not only how to detect shockwaves, but also how to obtain shockwaves from three new traffic parameters: Stopped, Moving, and Empty. The Stopped parameter attempts to identify a newly arrived shockwave equation when a traffic queue approaches the electronic vehicle detector. The Moving and Empty parameters derive another new arrival shockwave equation when the electronic vehicle detector fails to identify any queue. An algorithm is also created to demonstrate how to use these parameters and equations to detect shockwaves. Additionally, numerous simulations are conducted to identify the behaviors of new traffic parameters and the effectiveness of the proposed algorithm. Results of this study demonstrate that the computing algorithm for electronic vehicle detectors can accurately detect shockwaves.
Statistical queuing-length approach to system-on-chip signal control
(2005)
Jou, Yow-Jen
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Tseng, Ming-Te
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統計學研究所
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Institute of Statistics
The chief goal of this paper is to describe a methodology for predicting the dynamic queue length of traffic signal control system on chip (SoC). There are two key steps. The first is to predict the dynamic traffic volumes for an oversaturated traffic intersection's link. This step is to fit a censored model for the traffic flow by using the historical relevant information of traffic flow, including past volumes and occupancy data. Then, the predicted traffic volumes will be cumulated to predict the queue length. Also, algorithm has been developed and a sample is given to verify the model.
Using detection of vehicular presence to estimate shockwave speed and upstream traffics for a signalized intersection
(2014-04-01)
Cho, Hsun-Jung
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Tseng, Ming-Te
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Hwang, Ming-Chorng
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運輸與物流管理系註：原交通所+運管所
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友訊交大聯合研發中心
Based on the Lighthill-Whitham-Richards (LWR) traffic flow theory, this paper provides alternative methods to compute shockwave speed mainly by using detection data that reflects three states of vehicular presences: vehicles in moving, vehicles stopped, and void of vehicles. As the duration of a state is firmly identified within a cycle, the proposed methods compute shockwave speeds directly by means of Euclidian geometrics on time-space trajectory of shockwaves. This approach is also applicable to congested signal links with a long queue (but a residual queue) beyond detection zone. In addition, given signal timing and the shockwave speeds calculated by the methods, characteristics of arrival traffics, i.e. upstream flow rate and speed, can be predicted before the end of current cycle. It justifies that the methods are capable of whether to extend green phase before next cycle or not and will be a promising tool for real-time operations of signal control. Finally, the predicted shockwave speeds, upstream flow rate, and space mean speed by the proposed method are testified using simulated data from CORSIM. The mean absolute percentage errors of the estimated speeds of forward recovery shockwave and backward forming shockwave are 4.0% and 12.4% respectively. For the predicted flow rate and space mean speed of downstream arrival traffics, the mean absolute percentage errors are 18% and 4%, respectively. The results demonstrate the effectiveness of the presented approach. (C) 2014 Elsevier Inc. All rights reserved.