Research On Train Speed Curve Optimization Algorithm Based On GA-SPSO Algorithm

Urban rail trains were used as an important inter-city transport,the rapid development momentum in recent years. In order to ensure the safe operation of urban rail train, on time and improve its transportation efficiency, so as to meet the passenger comfort and respond to the call of social environmental protection and energy conservation, it is urgent to study the running speed curve of train. However, in the past few years at home and abroad in the train automatic operation ( Automatic Train Operation, ATO ) control strategy research and optimization are mostly for specific indicators to carry out, did not consider a number of target optimization situation, the effect is not ideal.At present, in order to improve the train transportation efficiency and improve the automatic operation strategy, the companies and scholars of the countries have started to study the automatic speed curve optimization of the train. However, considering the train control strategy in the train running process is difficult In addition, the multi- objective,complex and non-linearity of the train running process makes it difficult to determine the exact model and the optimal velocity curve. However,the artificial intelligence technology and the hybrid optimization theory are rapid. Development for the train automatic operation control strategy research and innovation provides a new opportunity.This paper mainly focuses on the optimization of train speed curve,first analyzes the optimization rules of train operation control strategy and train running time, combines the performance index evaluation system of automatic running speed curve, establishes the evaluation index of each index (AHP) and entropy (Entropy) method are used to determine the weight distribution of each performance index. Then,combined with the train's own parameters and running line conditions,the model of the evaluation index is established. The evaluation index model is established by using the Analytic Hierarchy Process (AHP) and Entropy method. The results show that the optimization strategy based on GA-SPSO algorithm is better than that based on GA-SPSO algorithm,and the optimization strategy based on GA-SPSO algorithm is used to optimize the train running speed curve. Finally, Genetic algorithm optimization strategy to achieve the automatic operation of the train in accordance with the given the most suitable for the given operating environment and running the speed curve. This ensures that the train in the safe driving under the premise of ensuring the train on time, accurate parking, reduce energy consumption and passenger comfort and other performance requirements.