Research on Intelligent Schedule of Public Traffic Vehicles based on Genetic Algorithm
The paper studies bus intelligent scheduling problem,and builds mathematical model,at the same time taking into consider the passengers travel efficiency and the bus company benefits,gives the genetic algorithm to solve this problem.In the method,the focuses are on the objective function of intelligent schedule problem,fitness function and genetic operators design.Through program for simulation experiment,the results show that using genetic algorithms to solve the intelligent scheduling problems can optimize the vehicle scheduling and arrange uneven schedule at the peak and low peak period,and conform to the public and bus company interests,therefore improve the efficiency of traffic operations.
We present a method for synthesising control strategies for continuous dynamical systems. We use Uppaal Tiga for the synthesis in combination with a set-based Euler method for guaranteeing that the synthesis is safe. We present both a general method and a method which provides tighter bounds for monotone systems. As a case-study, we synthesize a guaranteed safe strategy for a simplified adaptive cruise control application. We show that the guaranteed strategy is only slightly more conservative than the strategy generated in the original adaptive cruise control paper which uses a discrete non guaranteed strategy. Also, we show how reinforcement learning may be used to obtain optimal sub-strategies.