Investigating the Efficacy of In-Process Feedback in Improving Human-Machine Interaction in Autonomous Vehicles

As autonomous vehicles become more prevalent on our roads, the improvement of human-machine interaction (HMI) becomes increasingly critical. In-process feedback has emerged as a promising approach to enhancing HMI in autonomous vehicles, but limited research exists on its effectiveness. The purpose of this study is to determine how effective in-process feedback is at enhancing HMI. To investigate the impact of in-process feedback on HMI, a within-subjects approach and a quasi-experimental design were used. Ninety participants with experience driving autonomous vehicles were recruited and divided into an investigational group receiving in-process feedback and a control group without such feedback. The study measured the efficacy of in-process feedback on HMIs through subjective and objective measures. The subjective measure utilized a questionnaire to assess participants' perceptions of their driving experience, including comfort, confidence, and trust in the autonomous vehicle. The objective measure analyzed participants' driving behavior, encompassing speed, lane keeping, and steering patterns. The experimental group outperformed the control group in terms of comfort, confidence, and trust in the driverless car, according to the results. The objective measure also indicated improved driving behavior in the investigational group, including smoother lane keeping and fewer instances of sudden braking and acceleration. In conclusion, this study supports the effectiveness of in-process feedback as an approach to enhancing HMI in autonomous vehicles. The findings have practical implications for the design and development of autonomous vehicle technology, ultimately contributing to the public's acceptance and adoption of this technology.