Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/62546
Title: Online rescheduling of mass rapid transit systems: Fuzzy expert system approach
Authors: Chang, C.S. 
Thia, B.S.
Keywords: Fuzzy control
Fuzzy expert system
Rapid transit systems
Issue Date: 1996
Citation: Chang, C.S.,Thia, B.S. (1996). Online rescheduling of mass rapid transit systems: Fuzzy expert system approach. IEE Proceedings: Electric Power Applications 143 (4) : 307-314. ScholarBank@NUS Repository.
Abstract: The paper is concerned with the online rescheduling of mass rapid transit (MRT) trains after sudden increases of passenger flow. In particular, the use of predictive fuzzy control (PFC) for carrying out the train dwell-time control in an event-driven framework is considered. Two fuzzy expert systems for improving the performance of MRT systems and for enhancing functions of the typical automatic train control (ATC) systems are proposed. Using the event-driven approach, 'the only decisions to be made in each of the two fuzzy expert systems will be whether or not to dispatch the train at a proposed reschedule time. Due to its simplicity, the proposed methodology is fast enough for online implementation. An object-oriented environment has been developed for implementing the control and simulation algorithms that reduces the efforts required for understanding the interactive operation of railway subsystems and for preparing study data. Therefore, the efforts for future development will be reduced. The proposed approach is used for adjusting the train dwell time and for studying the effects on the MRT performance. Results show that the train dwell time adjustment is an effective means of maintaining the quality of train service after sudden load disturbances. Several simulated case studies are included to illustrate the effectiveness of the proposed approach. © IEE, 1996.
Source Title: IEE Proceedings: Electric Power Applications
URI: http://scholarbank.nus.edu.sg/handle/10635/62546
ISSN: 13502352
Appears in Collections:Staff Publications

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