The Effect of Multifactor Interaction on the Quality of Human–Machine Co-Driving Vehicle Take-Over

Yaxi Han, Tao Wang (), Dong Shi, Xiaofei Ye and Quan Yuan
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Yaxi Han: Guangxi Key Laboratory of Intelligent Transportation System, Guilin University of Electronic Technology, Guilin 541004, China
Tao Wang: Guangxi Key Laboratory of Intelligent Transportation System, Guilin University of Electronic Technology, Guilin 541004, China
Dong Shi: Guangxi Key Laboratory of Intelligent Transportation System, Guilin University of Electronic Technology, Guilin 541004, China
Xiaofei Ye: Faculty of Maritime and Transportation, Ningbo University, Ningbo 315211, China
Quan Yuan: State Key Laboratory of Automotive Safety and Energy, School of Vehicle and Mobility, Tsinghua University, Beijing 100084, China

Sustainability, 2023, vol. 15, issue 6, 1-16

Abstract: This paper investigates the effects of non-driving related tasks, take-over request time, and take-over mode interactions on take-over performance in human–machine cooperative driving in a highway environment. Based on the driving simulation platform, a human–machine collaborative driving simulation experiment was designed with various take-over quality influencing factors. The non-driving related tasks included no task, listening to the radio, watching videos, playing games, and listening to the radio and playing games; the take-over request time was set to 6, 5, 4, and 3 s, and the take-over methods include passive and active take-over. Take-over test data were collected from 65 drivers. The results showed that different take-over request times had significant effects on driver take-over performance and vehicle take-over steady state ( p < 0.05). Driver reaction time and minimum TTC decreased with decreasing take-over request time, maximum synthetic acceleration increased with decreasing take-over request time, accident rate increased significantly at 3 s take-over request time, and take-over safety was basically ensured at 4 s request time. Different non-driving related tasks have a significant effect on driver take-over performance ( p < 0.05). Compared with no task, non-driving related tasks significantly increase driver reaction time, but they only have a small effect on vehicle take-over steady state. Vehicle take-over mode has a significant effect on human–machine cooperative driving take-over quality; compared with passive take-over mode, the take-over quality under active take-over mode is significantly lower.

Keywords: human–machine cooperative driving; multi-factor interaction; driver take-over performance; vehicle take-over steady state (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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