Title :
Application of Genetic Algorithm in Automatic Train Protection
Author :
Liu Xiao ; Zhang Ya-Dong ; Guo Jin
Author_Institution :
Sch. of Inf. Sci. & Technol., Southwest Jiaotong Univ., Chengdu, China
Abstract :
Automatic train protection plays an important role in high-speed railway, to implement this function, train braking mode curve must be derived. The programming logic of traditional braking mode curve arithmetic is complex, and its precision is not enough. To overcome these shortcomings, a braking mode curve arithmetic Based on curve fitting using genetic algorithm is proposed. Fit train braking characteristic data, use the kinematic formula for calculus calculation, and then braking distance-velocity function is derived, therefore braking mode curve can easily be obtained. Matlab is used for calculation. Compare the process and result of this new method with the traditional one, we can find this method is more simple and precise.
Keywords :
braking; calculus; curve fitting; genetic algorithms; kinematics; logic programming; railway engineering; automatic train protection; braking mode curve arithmetic; calculus calculation; curve fitting; genetic algorithm; high-speed railway; kinematic formula; programming logic; Control systems; Curve fitting; Educational institutions; Equations; Genetic algorithms; Mathematical model; Rail transportation; braking distance; braking mode curve; calculus calculation; curve fitting; genetic algorithm;
Conference_Titel :
Intelligent Human-Machine Systems and Cybernetics (IHMSC), 2013 5th International Conference on
Conference_Location :
Hangzhou
Print_ISBN :
978-0-7695-5011-4
DOI :
10.1109/IHMSC.2013.183