Research On Human-machine Interaction Mode For High-speed Train With Situation Awareness Enhancement

The trains may encounter unpredictable and special circumstances such as software or hardware failures,emergencies while in automatic model.The driver will then be required to manually take over the automatic train.The level of situation awareness of the driver is related to the takeover performance and driving safety.Based on the background that high-speed train is becoming more and more automated and intelligent,this study is dedicated to maintaining and improving the driver’s situation awareness during long hours of operation by optimizing the human-machine interaction mode.The paper firstly use the cognitive work analysis framework to analyze the speed control tasks during the operation of high-speed trains.Then we analyzes the causal factors for the driver’s lack of situation awareness in automatic driving mode,and proposes a dynamic situation awareness circle model and a human-computer interaction model for situation awareness enhancement.In the last,we completed experimental validation.The main research work and results of this paper are described as follows:(1)Completed the analysis of the causes of situation awareness deficiency of highspeed train drivers.Based on situation awareness model from Endsley’s research,we analyzed the differences in drivers’ cognitive tasks between manual and automatic driving modes with the cognitive work analysis framework.The analysis revealed that due to the shift in driving tasks,drivers have difficulty spontaneously completing cognitive activities such as perception,comprehension,and prediction related to the driving task in autonomous driving mode,and hard to maintain a good level of situation awareness.(2)Dynamic situation awareness circle model applicable to high-speed train drivers was proposed.This model described the cognitive state in which a driver with a good situation awareness state was in.The cyclical process of maintaining the driver in the cognitive states of perception,comprehension,and prediction,driven by cognitive resources and mental models.(3)A human-machine interaction model for high-speed train speed control tasks oriented to situation awareness enhancement was proposed.For the interval operation speed control task,the task was divided into three stages,namely information acquisition and analysis,decision generation,and behavior implementation according to the information processing model,and defined as the human-machine public workspace.The paper also implemented a design example of the above human-machine interaction model by modifying the DMI interface.(4)Experimental validation of the effectiveness of the human-machine interaction model for situation awareness enhancement was carried out.The experimental system of human-machine interaction mode for high-speed trains based on a driving simulator was designed and implemented,and human factors experiments were conducted to compare and analyze the effects of the current automatic driving mode and the human-machine interaction mode for situation awareness enhancement on situation awareness,workload,driving performance,and prefrontal oxyhemoglobin and other indicators reflecting the driver’s state.The experimental results show that,compared with the current automatic driving mode,the human interaction mode with situation awareness enhancement can increase the driver’s task involvement without increasing the workload,which puts the driver in the control loop and enhances the driver’s situation awareness during the long driving period,and verifies the effectiveness of the human-machine interaction mode with situation awarenes enhancement.The research results was of great significance to ensure the safety of high-speed trains.