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典型文献
Efficient normalization for quantitative evaluation of the driving behavior using a gated auto-encoder
文献摘要:
Driving behavior normalization is important for a fair evaluation of the driving style. The longitudinal control of a vehicle is investigated in this study. The normalization task can be considered as mapping of the driving behavior in a different environment to the uniform condition. Unlike the model-based approach as in previous work, where a necessary driver model is employed to conduct the driving cycle test, the approach we propose directly normalizes the driving behavior using an auto- encoder (AE) when following a standard speed profile. To ensure a positive correlation between the vehicle speed and driving behavior, a gate constraint is imposed in between the encoder and decoder to form a gated AE (gAE). This approach is model-free and efficient. The proposed approach is tested for consistency with the model-based approach and for its applications to quanti-tative evaluation of the driving behavior and fuel consumption analysis. Simulations are conducted to verify the effectiveness of the proposed scheme.
文献关键词:
作者姓名:
Xin HE;Zhe ZHANG;Li XU;Jiapei YU
作者机构:
College of Electrical Engineering,Zhejiang University,Hangzhou 310027,China
引用格式:
[1]Xin HE;Zhe ZHANG;Li XU;Jiapei YU-.Efficient normalization for quantitative evaluation of the driving behavior using a gated auto-encoder)[J].信息与电子工程前沿(英文),2022(03):452-462
A类:
gAE
B类:
Efficient,normalization,quantitative,evaluation,driving,behavior,using,auto,encoder,Driving,important,fair,style,longitudinal,control,vehicle,investigated,this,study,task,can,considered,mapping,different,environment,uniform,condition,Unlike,model,approach,previous,work,where,necessary,driver,employed,cycle,directly,normalizes,when,following,standard,speed,profile,To,ensure,positive,correlation,between,constraint,imposed,decoder,This,free,efficient,proposed,tested,consistency,its,applications,fuel,consumption,analysis,Simulations,are,conducted,verify,effectiveness,scheme
AB值:
0.486283
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