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Citation |
Gao Y, Feng Z, Zhu D, Zeng J, Lu X, Huang Z, Gu T. Transp. Res. F Traffic Psychol. Behav. 2024; 103: 554-573. |
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Copyright |
(Copyright © 2024, Elsevier Publishing) |
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DOI |
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PMID |
unavailable |
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Abstract |
During human-machine codriving, drivers need to take over the vehicle when a take-over request (TOR) appears. If drivers have not received relevant training before driving, they may be unable to complete the take-over within the limited time, or the stability of subsequent vehicle control may be insufficient, which can lead to accidents. In this study, two types of take-over ability improvement methods are proposed. Participants were recruited and randomly divided into a control group (n = 15, no take-over training) and two experimental groups (n = 15, text-based training; n = 15, behavioral spectrum-based training). One-way ANOVA or the Kruskal-Wallis test and post hoc contrasts were used to analyze the differences in data indicators between the three groups of drivers after 20 take-over operations, and another method was proposed to validate the efficiency of the take-over operations on the stability of take-over ability. The results show that compared with the control group, both experimental groups demonstrated a significant improvement in take-over ability, with the behavioral spectrum-based training group exhibiting better take-over performance than the text-based training group. Moreover, after 14 take-over operations, drivers' take-over ability in the behavioral spectrum-based training group stabilized. The findings of this study can contribute to the safety of human-machine codriving vehicles and the design of future driver training systems. |
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Keywords |
Human–machine codriving; Improvement method; Steady-state analysis; Take-over ability |