Frontiers of Information Technology & Electronic Engineering
>> 2022,
Volume 23,
Issue 3
doi:
10.1631/FITEE.2000667
Efficient normalization for quantitative evaluation of the driving behavior using a gated auto-encoder
Received: 2020-11-28
Accepted: 2022-03-22
Available online: 2022-03-22
Next
Previous
Abstract
is important for a fair evaluation of the driving style. The longitudinal control of a vehicle is investigated in this study. The task can be considered as mapping of the 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 using an auto-encoder (AE) when following a standard speed profile. To ensure a positive correlation between the vehicle speed and , 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 of the and fuel consumption analysis. Simulations are conducted to verify the effectiveness of the proposed scheme.
京公网安备 11010502051620号
