最大Lyapunov指数的车头间距预测方法分析

Analysis About Car’s Head Distance Prediction Method Based on Maximum Lyapunov Index

根据一维变量混沌时间序列的最大Lyapunov指数的预测思想,分析了基于最大Lyapunov指数的车头间距预测方法,该方法根据跟驰车量行驶达到混沌状态时的最大Lyapunov指数和随时间产生的一维具有混沌特性的历史车头间距序列进行预测。为了说明预测方法的可行性,又在Bierley非线性跟驰模型下进行了仿真车流生成、混沌特性识别及算例验证等实验。实验结果表明,该方法理论上能对具有混沌特性的Bierley非线性跟驰模型的车头间距进行预测,可以为智能交通中车辆跟驰行驶模型安全预警提供理论参考。

According to the prediction of the largest Lyapunov exponent in one-dimensional variable chaotic time series,the paper analyzes the method of vehicle headway prediction based on the maximum Lyapunov exponent.According to the maximum Ly apunov exponent and the time-Dimensional chaotic characteristics of the history and front spacing of the sequence to forecase,in order to demonstrate the feasibility of the forecasting method,experiments are also carried out on the simulation of traffic flow gener ation,c haotic property identification and case verification under the Bierley nonlinear car-following model.Experimental results show that this method can theoretically predict the headway of the Bierley nonlinear model with chaotic characteristics and provide a theoretical reference for the safety warning of vehicle-following driving model in intelligent transportation.