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基于混合粒子滤波的高速公路交通参数自适应估计方法

, PP. 141-146

Keywords: 交通工程,高速公路,交通流,交通参数估计,混合粒子滤波,自适应调整

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Abstract:

为提高高速公路交通参数的估计准确度,在宏观交通流模型和状态空间模型的基础上,基于贝叶斯理论,提出了一种基于混合粒子滤波的交通参数估计方法。考虑到估计结果对模型参数变化的敏感性,避免采用预设固定模型参数对估计准确度的影响,通过建立自由流速度与饱和度之间的变化关系,提出了交通状态影响下的模型参数自适应调整策略。仿真结果表明基于混合粒子滤波的交通参数估计准确度要明显高于卡尔曼滤波估计,在正常和事故场景下,能够快速识别交通量和速度较明显的波动,表现出了更强的稳定性;交通状态影响下的模型参数自适应调整策略会明显提高交通参数估计准确度,在发生事故情况下,也可达到较好的估计效果。

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