Hierarchical Recognition Method for Driving Intent Based on Single-Pedal Control

The single-pedal mode control significantly impacts the driving performance, energy efficiency, and comfort of electric vehicles (EVs). As a novel integrated pedal system, changes in system characteristics and working modes demand higher requirements for optimizing human-machine characteristics. This paper starts with the unique braking logic of the single pedal and solves the complex intent recognition problem hierarchically based on the driver’s compression of functional areas. Ultimately, we propose a hierarchical active recognition model for single-pedal intent: RBF-GMM-HMM. By applying a hierarchical approach, this model addresses the complex intent recognition challenges of the single pedal. Simulation results demonstrate that the proposed RBF-GMM-HMM model effectively identifies the braking intent of the single pedal, outperforming traditional methods.

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Publication Details

Published
2024-10-25
DOI
https://doi.org/10.1109/icemce64157.2024.10862044
Primary Topic
Autonomous Vehicle Technology and Safety
Type
article
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article

Hierarchical Recognition Method for Driving Intent Based on Single-Pedal Control

Xiaohui Yuan, Haoliang Li, Xun Wang
Autonomous Vehicle Technology and Safety
article

Hierarchical Recognition Method for Driving Intent Based on Single-Pedal Control

Xiaohui Yuan, Haoliang Li, Xun Wang
article en

Abstract

The single-pedal mode control significantly impacts the driving performance, energy efficiency, and comfort of electric vehicles (EVs). As a novel integrated pedal system, changes in system characteristics and working modes demand higher requirements for optimizing human-machine characteristics. This paper starts with the unique braking logic of the single pedal and solves the complex intent recognition problem hierarchically based on the driver’s compression of functional areas. Ultimately, we propose a hierarchical active recognition model for single-pedal intent: RBF-GMM-HMM. By applying a hierarchical approach, this model addresses the complex intent recognition challenges of the single pedal. Simulation results demonstrate that the proposed RBF-GMM-HMM model effectively identifies the braking intent of the single pedal, outperforming traditional methods.

Nanjing University of Aeronautics and Astronautics (CN)
Openalex Percentile: Top 70%
Autonomous Vehicle Technology and Safety
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Hierarchical Recognition Method for Driving Intent Based on Single-Pedal Control — Xiaohui Yuan, Haoliang Li, et al. · (2024) | TGRS Research Map | TGRS