Browsing by Author "Huang, Yen-Fei"

Now showing 1 - 6 of 6

DEVELOPMENT OF OPTIMAL VARIABLE SPEED-LIMIT CONTROL MODEL
(2009)
Chiou, Yu-Chiun
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Lan, Lawrence W.
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Lin, Po-Cheng
;
Huang, Yen-Fei
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運輸與物流管理系註：原交通所+運管所
Application of variable speed-limit (VSL) control has become promising in managing the incidents in the contexts of intelligent highway systems wherein advanced VSL signs are densely placed along the roadways. This paper aims to develop a genetic-fuzzy-logic-controller (GFLC)-based VSL control model with an objective function to enhance both safety and throughput efficiency at the incident sites. In order to evaluate the performance of learned logic rules and tuned membership function, a revised cell transmission model (CTM) is proposed, which is validated with field traffic data. The results indicate that the proposed VSL control model can effectively curtail the crash likelihood without deteriorating or only slightly decreasing the throughput efficiency under different tested incident cases. It suggests that our proposed GFLC-based VSL control model is promising for practical applications.
GENETIC FUZZY LOGIC TRAFFIC SIGNAL CONTROL WITH A STEPWISE LEARNING ALGORITHM
(2010)
Chiou, Yu-Chiun
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Huang, Yen-Fei
;
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 an adaptive traffic signal control model based on a stepwise genetic fuzzy logic controller (SGFLC). The proposed model considers traffic flow and queue length as state variables and extension of green time as control variable, towards the minimization of total vehicle delays. For the learning efficiency of SGFLC and the capability in capturing traffic behaviors, cell transmission model (CTM) is used to replicate traffic behaviors. To investigate the performance of the proposed model at an isolated intersection, comparisons to three pre-timed and two adaptive signal timing models are also conducted. Results show that in both cases, our proposed SGFLC model almost achieved the optimal control. As traffic flows vary more noticeably, the SGFLC model performs even better. In the case of sequential intersections with four coordinated signal systems: simultaneous, progressive, alternate and independent, the results also show that the proposed SGFLC model can also perform best, suggesting that the proposed SGFLC signal control model is effective, robust and applicable.
Genetic fuzzy logic traffic signal control with cell transmission modeling
(2014)
Chiou, Yu-Chiun
;
Huang, Yen-Fei
;
運輸與物流管理系註：原交通所+運管所
;
Department of Transportation and Logistics Management
This study develops an adaptive traffic signal control model based on an iterative genetic fuzzy logic controller (GFLC). The proposed model considers traffic flow and queue length as state variables and extension of green time as control variable, toward the minimization of total vehicle delays. For the learning efficiency of GFLC and the capability in capturing traffic behaviors, cell transmission model is used to replicate the traffic condition. To investigate, the performance of the proposed model in the case of an isolated intersection, comparisons to pretimed signal timing plans determining by Webster and total enumeration methods, and two queue-length based adaptive models are conducted. Results show that our proposed GFLC model performs best. As traffic flows vary more noticeably, the GFLC traffic signal control model performs even better than any timing plans. In the case of sequential intersections with four coordinated signal systems: simultaneous, progressive, alternate, and independent, the experimental example study also show that the proposed GFLC model can also perform better than current and pretimed timing plans, suggesting that the proposed GFLC signal control model is effective, robust, and adaptable.
Optimal variable speed-limit control under abnormal traffic conditions
(2012-04-01)
Chiou, Yu-Chiun
;
Huang, Yen-Fei
;
Lin, Po-Cheng
;
運輸與物流管理系註：原交通所+運管所
;
Department of Transportation and Logistics Management
Application of variable speed-limit (VSL) control has become promising in managing incidents in the context of intelligent highway systems, wherein advanced VSL signs are densely placed along the roadways. This paper aims to develop a genetic-fuzzy-logic-controller (GFLC)-based VSL control model with an objective function to enhance both safety and throughput efficiency at incident sites. In order to evaluate the performance of learned logic rules and tuned membership function, a revised cell transmission model is proposed, which is validated with field traffic data. The results indicate that the proposed VSL control model can effectively curtail crash likelihood while only slightly decreasing the throughput efficiency under different tested incident cases. It suggests that our proposed GFLC-based VSL control model is promising for practical applications.
Stepwise genetic fuzzy logic signal control under mixed traffic conditions
(2013-01-01)
Chiou, Yu-Chiun
;
Huang, Yen-Fei
;
運輸與物流管理系註：原交通所+運管所
;
Department of Transportation and Logistics Management
This paper proposes a stepwise genetic fuzzy logic controller (SGFLC) by considering traffic flows and queue lengths of cars and motorcycles as state variables and extension of green time as control variable, towards the minimization of total vehicle delays. For the learning efficiency of SGFLC and the capability in capturing traffic behaviors of Asian urban streets, where mixed traffic of cars and motorcycles are prevailing, the mixed traffic cell transmission model (MCTM) is introduced to replicate traffic behaviors. To investigate the control performance of the proposed SGFLC model, comparisons with two pre-timed timing plans and three adaptive signal timing models are conducted at an isolated intersection. Results show our proposed SGFLC model performs best. Moreover, as traffic flows vary more noticeably, the SGFLC model performs even better. In the experimental and field cases of three-intersection arterial under four coordinated signal systems, namely simultaneous, progressive, alternate and independent, both cases consistently show that the proposed SGFLC model perform best, suggesting that the proposed SGFLC signal control model is efficient and robust. Copyright (c) 2012 John Wiley & Sons, Ltd.
TRAFFIC RESPONSIVE SIGNAL CONTROL SYSTEM UNDER MIXED TRAFFIC CONDITIONS
(2011-01-01)
Chiou, Yu-Chiun
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Lan, Lawrence W.
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Huang, Yen-Fei
;
Hsieh, Chih-Wei
;
交大名義發表
This paper develops an adaptive traffic signal control model based on a stepwise genetic fuzzy logic controller (SGFLC). The proposed model considers traffic flows and queue lengths of cars and motorcycles as state variables and extension of green time as control variable towards the minimization of total vehicle delays. For the learning efficiency of SGFLC and the capability in capturing traffic behaviors of Asian urban streets where mixed traffic of cars and motorcycles is prevailing, mixed traffic cell transmission model (MCTM) is also proposed to replicate traffic behaviors. To validate the performance of the proposed SGFLC model, comparisons to two enumeration pre-timed signal timing plans and two adaptive signal timing models are conducted. Results show that our proposed SGFLC model almost achieves the optimal control. As traffic flows vary more noticeably, the SGFLC model performs even better, suggesting that the proposed SGFLC signal control model is effective, robust and applicable.