中文摘要：

分析了驾驶员的操纵行为特性和轨迹决策模型的基本原理，指出了由于加速度增量式划分所带来的收敛性问题和评价指标隶属函数的非严格单调所带来的稳定性问题。在介绍优化方法基本原理的基础上，利用网格优化方法建立了汽车预期轨迹决策模型，并利用严格单调Sigmoid函数建立各个评价指标的隶属函数，消除了原有模型的不稳定和不收敛特性，为智能汽车方向决策控制的研究提供了一个更加合理的模型。

英文摘要：

This paper analyzed driver＇s behavior and essential principle of course decision, pointed out convergence problem caused by acceleration partition and stable problem caused by subjection function. The essential principles of optimization were introduced, based on which driver preview course model was given through gridding optimization. Relative subjection function by Sigmoid for its characteristics was established, and the problem of stable and convergence was eliminated. It provides an applicable way to the research of intelligent vehicle for direction decision and control.