Open AccessModeling and analysis of driver behaviour under shared control through weighted visual and haptic guidance
Author(s) -
Wang Zheng,
Zheng Rencheng,
Nacpil Edric John Cruz,
Nakano Kimihiko
Publication year - 2022
Publication title -
iet intelligent transport systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.579
H-Index - 45
eISSN - 1751-9578
pISSN - 1751-956X
DOI - 10.1049/itr2.12163
Subject(s) - haptic technology , process (computing) , weighting , driving simulator , simulation , trajectory , computer science , workload , steering wheel , matching (statistics) , visualization , engineering , artificial intelligence , automotive engineering , medicine , statistics , physics , mathematics , astronomy , radiology , operating system
Abstract Driver–automation shared control through haptic steering is developed to reduce the workload of drivers while keeping them in the control loop. For the optimum design of a haptic steering system, an understanding of driver behaviour based on measurements and modeling is crucial early in the development process. This paper aims to propose a driver model using a weighting process of visual guidance from the road ahead and haptic guidance from a steering system for a lane‐following task. The proposed weighting process describes the interaction and reliance of drivers in relation to haptic guidance steering. A driving simulator experiment is conducted to identify the model parameters for driving manually and with haptic guidance. The proposed driver model matched the driver input torque with reasonable fitness among 14 participants after considering individual differences. The validation results reveal that the output trajectory from the model effectively followed the driving course by matching the measured trajectory from the drivers. The model evaluation results reveal the potential of the proposed driver model to be applied to the design and evaluation of haptic guidance systems.