Correlation Analysis of Drivers’ Natural Driving Behavior Based on
Kernel Density Estimation
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Published:2023-06-09
Issue:2
Volume:4
Page:
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ISSN:2640-642X
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Container-title:SAE International Journal of Sustainable Transportation, Energy, Environment, & Policy
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language:en
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Short-container-title:SAE J. STEEP
Author:
Sun Tianjun,Hu Hongyu,Cai Ronggui,Yu Tong,Yu Feng
Abstract
<div>To investigate the interplay between driver handling behaviors, this article
collects data on vehicle kinematic parameters characterizing driver handling
characteristics under natural driving, estimates the probability density curves
of the parameters using the kernel density method, and fits the curve equations.
On this basis, a percentile correlation analysis was performed between the
parameters to obtain the influence relationship between the handling behaviors.
The results show that longitudinal maneuvers are frequent and intense in the
0–10 km/h speed range, lateral maneuvers are more intense in the 10–30 km/h
speed range, and the interaction between longitudinal and lateral maneuvers is
more intense in the acceleration phase. This study enriches the natural driving
dataset and illustrates the correlation of driving behavior under natural
driving, providing a theoretical and data basis for the development of
driver-oriented intelligent driving technologies.</div>
Publisher
SAE International
Subject
Management, Monitoring, Policy and Law,Engineering (miscellaneous),Aerospace Engineering,Transportation,Automotive Engineering,Renewable Energy, Sustainability and the Environment,Civil and Structural Engineering
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