冰雪环境下基于神经网络的驾驶人换道意图识别

doi:10.13229/j.cnki.jdxbgxb20210493

摘要/Abstract

摘要：

驾驶人驾驶汽车行驶过程会受到很多因素影响，不同的驾驶人相应的操作习惯不相同，不同路况驾驶方式也会不同。因此，本文对冰雪环境下行车特点进行分析，依据Carmaker搭建的半实物模拟驾驶仿真平台采集该条件下（包含对开路面）驾驶人行为参数以及车辆参数等数据，分析选取特征参数，建立数据样本库。基于神经网络建立意图识别模型，对模型分别从单一工况、复合工况进行验证，通过实验分析了模型性能，实验结果表明该模型能在对开路面准确识别驾驶人意图。

关键词: 交通运输系统工程, 驾驶人意图, 神经网络, 模拟驾驶, 仿真分析

Abstract:

The process of driving a car can be affected by many factors. Different drivers have different operating habits and different driving ways under different road conditions. Therefore， in this paper， driving characteristics in snow and ice covered environment were analyzed. Based on Carmaker， the hardware-in-the-loop driving simulation platform， data such as driver behavior parameters and vehicle parameters were collected under this condition （including the bifurcated road surface）， characteristic parameters were analyzed and selected， and data sample database was established. The intention recognition model was established based on neural network， and the model was verified in single condition and compound condition respectively. The performance of the model was compared and analyzed. It can be obtained that the model can accurately identify the driver's intention on the bifurcated road.

Key words: engineering of communication and transportation system, driver intention, neural network, driving simulation, the simulation analysis

中图分类号:

U491.2

卢辉遒,赵枫,谢波,田彦涛. 冰雪环境下基于神经网络的驾驶人换道意图识别[J]. 吉林大学学报(工学版), 2023, 53(1): 273-284.

Hui-qiu LU,Feng ZHAO,Bo XIE,Yan-tao TIAN. Driver's lane change intention recognition in snow and ice environment based on neural network[J]. Journal of Jilin University(Engineering and Technology Edition), 2023, 53(1): 273-284.

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