Trajectory prediction algorithm of unmanned vehicles at urban intersection based on edge computing

doi:10.3969/j.issn.1674-8484.2021.02.003

Abstract

Abstract:

A trajectory prediction algorithm was proposed based on the combination of driver intent classification and Bezier curve in the edge computing platform to provide prior information for unmanned vehicles to accurately formulate urban intersection trajectories. Proposed a support vector machine-based driver intention recognition algorithm to predict the probability of vehicles going straight, turning left or turning right at the intersection after analyzing the actual traffic data of 230 vehicles at two intersections. And proposed a traffic trajectory prediction method based on the combination of Bezier curve and cost function to predict the traffic trajectory of the intersection. The results show that the accuracy of the driver’s intention classification algorithm is above 92.5% comparing with the actual data collected from 120 vehicles. The maximum deviation range between the predicted trajectory of the vehicle and the true trajectory is 0.223~0.579 m. The average deviation between the predicted trajectory of all vehicles and the true trajectory is 0.214 m. Therefore, this method meets the needs of vehicle trajectory prediction at urban intersections.

Key words: unmanned vehicles, urban intersection transiting, trajectory prediction, driver intention recognition, edge computing

CLC Number:

U467.1+4

HAO Lulu, XIE Hui, SONG Kang, YAN Long. Trajectory prediction algorithm of unmanned vehicles at urban intersection based on edge computing[J]. Journal of Automotive Safety and Energy, 2021, 12(2): 163-172.

Figures/Tables 22

References 19

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硬件设备	性能指标	输出信息
激光雷达	水平视场角：360°;垂直视场角：30°; 最大测距：150 m;精度：±2 cm。	种类、ID、长宽高、速度、航向角、经纬度时间戳、相对角度、相对距离。
Xavier	内存：16 GB;CPU：8个;架构：ARM;接口：以太网/CAN、总线/串口/USB等。	处理激光雷达点云数据。

硬件设备	性能指标	输出信息
激光雷达	水平视场角：360°;垂直视场角：30°; 最大测距：150 m;精度：±2 cm。	种类、ID、长宽高、速度、航向角、经纬度时间戳、相对角度、相对距离。
Xavier	内存：16 GB;CPU：8个;架构：ARM;接口：以太网/CAN、总线/串口/USB等。	处理激光雷达点云数据。

输入特征向量		准确率/%
个数	种类	准确率/%
1	θ	58.7
1	Δα	40.7
1	v	20.8
1	Δd	22.8
2	(x, y)	69.6

输入特征向量		准确率/%
个数	种类	准确率/%
1	θ	58.7
1	Δα	40.7
1	v	20.8
1	Δd	22.8
2	(x, y)	69.6

输入特征向量		准确率/%
个数	种类	准确率/%
2	θ、Δα	76.6
3	(x, y)、θ	84.5
4	θ、Δα、v、Δd	83.4
4	(x, y)、θ、Δα	85.0
5	(x, y)、θ、Δα、v	91.2
5	(x, y)、θ、Δα、Δd	92.6
6	(x, y)、θ、Δα、Δd、v	92.1