| With the increasing number of driving automation systems mounted on modern vehicles,more and more frontier technologies are involved in the relevant systems,and the humanmachine interaction design and use process become more and more complex.There may be inconsistency between driver’s understanding of the system and designer’s expectations,which leads to more and more human-machine interaction errors and thus traffic accidents.With the improvement of driving automation level,the driver’s confidence in the system will be increased,even too much.The mistake of auxiliary driving as unmanned driving results in distracted driving or other non-driving tasks,which poses a potential threat to the life and safety of drivers and passengers and poses a major safety challenge.How to ensure the safety of automatic driving human-machine interaction is a key problem to be solved urgently at present.The United Nations Economic Commission for Europe（UNECE）issued the first regulation on the L3 Automated Lane Keeping Systems（ALKS）,which sets out detailed requirements for the functional specifications,Cybersecurity,Operational Design Domain and human-machine interaction of the ALKS system.In order to meet the above safety requirements and ensure the safety of human-machine interaction of Automatic Lane Keeping System,this paper,based on UNECE regulations,carries out the following research on human-machine interaction of ALKS system:Firstly,the safety analysis of human misuse in ALKS system is carried out.It includes defining the relevant items of ALKS and forming the initial structure of ALKS system as the basis of subsequent analysis;Based on the description of ALKS driver interaction function and the purpose of analysis according to STPA-1 definition,the potential vehicle-level hazard of accidents caused by human misuse of drivers is included.Identify driver-related unsafe control behaviors using STPA-3 guidewords and update vehicle-level hazards caused by iterations;Conduct hazard event identification and risk assessment and define acceptable risk criteria;Conduct the cause scenario analysis of unsafe control behavior and put forward the safety design requirements of takeover process as the basis for subsequent takeover strategy design and takeover interface design.Secondly,the safety design of takeover process is carried out based on the safety design requirements derived above,including the design of hierarchical warning human-machine interface and takeover strategy.Firstly,it elaborates the principle and process of humanmachine interface design,defines typical takeover scenarios,selects the media carrying the interface and designs the structure frame of takeover warning interface.Secondly,the requirements of takeover process safety design are refined and summarized for human-machine interface design and takeover strategy design of takeover process,and different levels of takeover interface design are completed when the automatic driving system sends takeover warning signal.Finally,the corresponding takeover strategies are designed according to the different driver States and input for the next takeover strategy verification.Finally,the takeover strategy is validated and the takeover performance is evaluated.First,use MATLAB/Simulink to design the takeover warning module and control switch module,and use Pre Scan to complete the design and construction of the experimental scene,and then carry out the joint simulation of the takeover process;Secondly,the evaluation method and key indicators of takeover performance are elaborated,and the experimental scheme is designed.Finally,the takeover warning platform is used to verify the rationality and effectiveness of takeover strategy design under driver distraction（such as playing games and chatting）.The effects of driver’s sub-task participation mode and sub-task immersion time on takeover performance are explored by takeover response time and maximum lateral acceleration.The human misuse safety analysis and evaluation and takeover strategy design of ALKS system in this paper have certain reference value for improving the safety of human-machine interaction and takeover design of automatic driving vehicles. |
