| 基于ANP-SVR的驾驶员能力预测模型设计 |
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| 引用本文： | 王时敏,孙涛.基于ANP-SVR的驾驶员能力预测模型设计[J].农业装备与车辆工程,2021(2). |
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| 作者姓名： | 王时敏 孙涛 |
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| 作者单位： | 上海理工大学机械工程学院 |
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| 摘 要： | 基于Prescan仿真平台搭建的驾驶场景,搭建了人机交互式的驾驶仿真系统进行数据采集实验,计算了驾驶能力判断中各评价指标因素的权重。通过ANP-SVR算法建立了驾驶能力预测模型,模型精度高,可以为实时驾驶能力预测的研究进行铺垫。基于熵权法计算驾驶风险度,通过比较驾驶风险度与驾驶能力评估的数据,得出数据的一致性,验证了ANP算法应用于驾驶员能力评估的可行性。
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| 关 键 词： | 驾驶能力 预测模型 ANP-SVR 网络分析法 |
Design of Driver Capability Prediction Model Based on ANP-SVR Algorithm |
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| Wang Shimin,Sun Tao.Design of Driver Capability Prediction Model Based on ANP-SVR Algorithm[J].Agricultural Equipment & Vehicle Engineering,2021(2). |
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| Authors: | Wang Shimin Sun Tao |
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| Institution: | (School of Mechanical Engineering,University of Shanghai for Science and Technology,Shanghai 200093,China) |
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| Abstract: | Based on the driving scenario built on the Prescan simulation platform,this paper develops a human-machine interactive driving simulation system to conduct data acquisition experiments,and calculates the weight of each evaluation index factor in the determination of driving ability.The driving ability prediction model was established by the ANP-SVR algorithm.The model has high accuracy and can pave the way for the research of real-time driving ability prediction.The driving risk is calculated based on the entropy weight method.By comparing the driving risk and driving ability evaluation data,the consistency of the data is obtained,which verifies the feasibility of the ANP algorithm for driving ability evaluation. |
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| Keywords: | driving ability prediction model ANP-SVR analytic network process |
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