Vehicle Trajectory Prediction with Integrating a Physics based Method and a Data-based Method

被引:0
|
作者
Choi, Wansik [1 ]
Ahn, Changsun [1 ]
机构
[1] Pusan Natl Univ, Busan, South Korea
来源
2019 AUSTRALIAN & NEW ZEALAND CONTROL CONFERENCE (ANZCC) | 2019年
基金
新加坡国家研究基金会;
关键词
D O I
10.1109/anzcc47194.2019.8945695
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The physics and data-based methods are used to predict the trajectory of vehicles. To improve prediction performance, we suggest data-based methods using a deep learning model and a simple integration method. The integration method is the weighted sum, and the weights are extracted from the root mean square error of two methods. It shows enhanced results by taking the strength of both methods. The root mean square error of 0 to 3 seconds is less than 3 meter, and 3 to 6 seconds is less than 6 meter.
引用
收藏
页码:203 / 203
页数:1
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