Browsing by Author "Kuo, AY"

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Color image vehicular detection systems with and without fuzzy neural network: A comparison
(2003-09-01)
Lan, LW
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Kuo, AY
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Huang, YC
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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
This paper develops a color image vehicular detection (CIVD) system in which background differencing technique is employed to detect whether a vehicle passes through the detecting points equally spaced out on a pseudo line detector. Two methods (interval search and regression) are tried to determine the optimal crisp threshold values to cope with various lighting conditions. To compare the detection performance with and without incorporating a fuzzy neural network (FNN), a three-layer FNNCIVD system is further designed with trapezoidal membership function and network parameters trained by back propagation algorithm. Under different environments (freeway and urban street) with various lighting conditions (daytime and nighttime), it is found that the detection success rates for interval-search CIVD and regression CIVD are about the same. However, both perform worse than the FNNCIVD system in which about 90% success rates are reported with seven detection points. Compared with the interval-search CIVD system, the FNNCIVD system can increase the success rates at a range of 14% to 22% on the freeway mainline and 18% to 26% on the urban street. It is also found that daytime detection performance is slightly better than nighttime detection. Possible reasons for missed detection and false detection are discussed.
Development and deployment of public transport policy and planning in Taiwan
(2006-03-01)
Lan, LW
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Wang, MT
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Kuo, AY
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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
Over the past decade, the escalating roadway congestion and environmental deterioration due to heavy use of private vehicles have provoked the Taiwan government to realize the importance of public transport systems. Under the "carrot-and-stick" rationales, the government has formulated public transport policies and exercised a series of related initiatives by providing sufficient and higher quality of public transport services so as to attract more private vehicle users. In this paper, the planning philosophy and policy formulation of Taiwan's public transport development are highlighted. The most important initiatives, including the Five-year Enhancement of Mass Transportation Program and the upgrading public transport schemes in the National Development Plan are examined. Based on previous experience and lessons, we point out the most challenging issues that the government will encounter. Suggestions for the future of public transport planning are also addressed.
Development of a fuzzy neural network color image vehicular detection (FNNCIVD) system
(2002)
Lan, LW
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Kuo, AY
;
運輸與物流管理系註：原交通所+運管所
;
Department of Transportation and Logistics Management
This paper develops a fuzzy neural network color image vehicular detection (FNNCIVD) system to detect the multiple-lane traffic flows. A pseudo line detector with fourteen detection points is placed on the monitor to detect the two-lane traffic images. On each detection point, the differencing of R, G and B pixel values between background Image and, Instantaneous Image are Inputted every one-tenth second Into a four-layer fuzzy neural network trained by the backpropagation algorithm. Traffic scenes in the daytime and nighttime are both experimented. The experiment results show that the success rates for traffic counting In different lighting conditions can be as high as 90%. in the mean time, the success rates for vehicle classification can reach 100%.
Modeling bus drivers' aberrant behaviors and the influences on fuel and maintenance costs
(2003-12-01)
Lan, LW
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Kuo, AY
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運輸與物流管理系註：原交通所+運管所
;
Department of Transportation and Logistics Management
Bus drivers' aberrant behaviors such as errors and violations might bring about extra fuel consumption and mechanic abrading. To investigate how the aberrant behaviors affect the fuel and maintenance costs, seven indexes are proposed and their corresponding threshold values are determined through the field experiments. Nearly six months of en route data are collected from an intercity bus route and the raw data are converted into the proposed index values by a database management system. A collinearity test is performed and three different specifications of simultaneous-equation regression models are attempted. The results show that abnormal engine rotation, unstable speed gradient, remarkable jerk, and speeding are the four independent indexes which can significantly explain the effects of bus drivers' aberrant behaviors on fuel and maintenance costs. Based on the cost importance of these four indexes, the drivers are further clustered into five categories and some practical applications are addressed.