Title page for etd-0710106-215736


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URN etd-0710106-215736
Author Kuo-Hua Sun
Author's Email Address No Public.
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Department Electrical Engineering
Year 2005
Semester 2
Degree Master
Type of Document
Language zh-TW.Big5 Chinese
Title Signaling Control and Timetable Planning for MRT Systems
Date of Defense 2006-06-26
Page Count 111
Keyword
  • Signaling Control
  • Abstract Automatic Train Control(ATC) of Signaling System for a Metro Systems comprise Automatic Train Supervision(ATS), Automatic Train Protection(ATP) and Automatic Train Operation(ATO). Based on theAutomatic Train Control(ATC) of Signaling System for a Metro Systems comprise Automatic Train Supervision(ATS), Automatic Train Protection(ATP) and Automatic Train Operation(ATO). Based on the Signaling Control System of Kaohsiung Mass Rapid Transit System(KMRT),the relationship of ATO propulsion power consumption and the run time between stations of train sets under the constraint of Automatic Train Protection(ATP) is investigated. By integrating the ATC function for the planning of timetable, the optimal timetable can be established.
    ATO solves the speed command for train sets operation by considering the propulsion system, track alignment and the operating timetable to achieve the efficiency of energy consumption by applying the operation modes of Cruising and Coasting to derive the speed profiles of train sets.
    Because of the correlationship of ATP, ATO and Operation Timetable of train sets, the ATP system is investigated first to ensure the safety of system operation. Based on the constraint of ATP, the energy conservation of train sets with ATO system is simulated. The optimal timetable is then derived by minimizing the objective function, which consists of the costs of train sets, driver’s manpower and the simulated energy consumption.
    The Genetic Algorithm (GA) is applied to solve the optimal timetable by representing the Run Time Reserve and Loading Factor of train sets as the chromosomes. With the mutation of GA method, the global optimal solution can be obtained without falling into the local optimum. It is concluded that the optimal operation timetable solved by the proposed GA method can enhance the system performance of KMRT systems by reducing the operation cost of train sets.
    Advisory Committee
  • Chen-Chiu Chang - chair
  • Jaw-Shyang Wu - co-chair
  • Hui-Jen Chuang - co-chair
  • Chao-Shun Chen - advisor
  • Files
  • etd-0710106-215736.pdf
  • indicate in-campus access in a year and off_campus not accessible
    Date of Submission 2006-07-10

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