Research on Running Curve Optimization of Automatic Train Operation System Based on Genetic Algorithm
| Autor: | Zhengmin Ren, Guanlei Wang, Hao Liu, Cunyuan Qian |
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| Rok vydání: | 2018 |
| Předmět: |
050210 logistics & transportation
Urban rail transit Computer science business.industry media_common.quotation_subject 05 social sciences Energy consumption Multi-objective optimization Punctuality Automatic train operation 0502 economics and business Genetic algorithm MATLAB business computer 050203 business & management Simulation media_common computer.programming_language Graphical user interface |
| Zdroj: | Lecture Notes in Electrical Engineering ISBN: 9789811079856 |
| DOI: | 10.1007/978-981-10-7986-3_91 |
| Popis: | The running curve optimization of automatic train operation (ATO) system usually takes into account running time, energy consumption and passenger comfort. In this paper, in order to provide more comprehensive optimization and accurate reference of running curve for ATO system, we adopted the multi-objective optimization strategy of genetic algorithm (GA) to optimize from five aspects: speeding (safety), parking accuracy, punctuality, energy consumption and comfort. The GA optimization program is written by M language in MATLAB, and combined with a graphical user interface (GUI) tool to design the optimization system of running curve of ATO based on genetic algorithm. Its validity is verified by comparison between the tests based on three different interstation of Shanghai Metro Line 11. The results show that it is effective and practicability to use the designed system to optimize the running curve of ATO system. |
| Databáze: | OpenAIRE |
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