ISSN 1671-3710
CN 11-4766/R

Advances in Psychological Science ›› 2021, Vol. 29 ›› Issue (12): 2172-2183.doi: 10.3724/SP.J.1042.2021.02172

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Trust in automated vehicles

GAO Zaifeng1(), LI Wenmin1, LIANG Jiawen1, PAN Hanxi1, XU Wei2, SHEN Mowei1   

  1. 1Department of Psychology and Behavioral Sciences, Zhejiang University, Hangzhou 310007, China
    2Center for Psychological Sciences at Zhejiang University, Hangzhou 310007, China
  • Received:2020-12-27 Published:2021-10-26
  • Contact: GAO Zaifeng


Automated driving (AD) is one of the key directions in the intelligent vehicles field. Before full automated driving, we are at the stage of human-machine cooperative driving: Drivers share the driving control with the automated vehicles. Trust in automated vehicles plays a pivotal role in traffic safety and the efficiency of human-machine collaboration. It is vital for drivers to keep an appropriate trust level to avoid accidents. We proposed a dynamic trust framework to elaborate the development of trust and the underlying factors affecting trust. The dynamic trust framework divides the development of trust into four stages: dispositional, initial, ongoing, and post-task trust. Based on the operator characteristics (human), system characteristics (automated driving system), and situation characteristics (environment), the framework identifies potential key factors at each stage and the relation between them. According to the framework, trust calibration can be improved from three approaches: trust monitoring, driver training, and optimizing HMI design. Future research should pay attention to the following four perspectives: the influence of driver and HMI characteristics on trust, the real-time measurement and functional specificity of trust, the mutual trust mechanism between drivers and AD systems, and ways in improving the external validity of trust studies.

Key words: trust, automated driving, dynamic trust framework, trust calibration, HMI design

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