A Stochastic Approach for Modeling Lane-Change Trajectories
A Stochastic Approach for Modeling Lane-Change Trajectories
复制标题
车道变换轨迹建模的随机方法
DOI：
10.1007/978-1-4419-9607-7_19
复制
发表时间：
2012
期刊：
影响因子：
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通讯作者：
K. Takeda
中科院分区：
文献类型：
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作者：
Y. Nishiwaki;C. Miyajima;N. Kitaoka;K. Takeda
讨论了一种在驾驶过程中变换车道期间对车辆轨迹进行建模的信号处理方法。由于个人驾驶习惯不是一个确定性过程，因此我们开发了一种随机方法来对其进行建模。所提出的模型由两部分组成：由隐马尔可夫模型表示的动态系统和由危险图函数表示的认知距离空间。第一部分对车辆运动的局部动力学进行建模并生成一组可能的轨迹。第二部分通过随机评估与周围车辆的距离来选择最佳轨迹。通过实验评估，我们表明该模型可以预测给定交通条件下的车辆轨迹，预测误差为17.6m。
A signal-processing approach for modeling vehicle trajectory during lane changes while driving is discussed. Since individual driving habits are not a deterministic process, we develop a stochastic method to model them. The proposed model consists of two parts: a dynamic system represented by a hidden Markov model and a cognitive distance space represented with a hazard-map function. The first part models the local dynamics of vehicular movements and generates a set of probable trajectories. The second part selects an optimal trajectory by stochastically evaluating the distances from surrounding vehicles. Through experimental evaluation, we show that the model can predict vehicle trajectory in given traffic conditions with a prediction error of 17.6m.
DOI：
10.1109/icassp.2000.861820
发表时间：
2000-06
期刊：
2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100)
影响因子：
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作者：
K. Tokuda;Takayoshi Yoshimura;T. Masuko;Takao Kobayashi;T. Kitamura
通讯作者：
K. Tokuda;Takayoshi Yoshimura;T. Masuko;Takao Kobayashi;T. Kitamura