Traffic sign recognition task cognitive integration model based on the ACT-R cognitive structure

The drivers' faults on cognition, decision-making, and operation are considered as important factors that lead to traffic accidents in the progress of reading signs. However, the mechanism of driver's cognitive processes and decision making with the high driving workload in a complex environment are still unclear, and the prevention of accident is not efficiency. This paper aims to identify the cognitive and decision-making mechanism of the driver with different signs reading load. First of all, complex environmental characteristics of hazardous locations were analyzed based on the actual highway accident data statistical analysis; Secondly, different driving scene and driving tasks were designed, driving simulator was employed as a platform to carry out experiments to test the drivers' psychology, and the data synchronization technology was used to collect all kinds of data; Thirdly, ACT-R modeling technology was implemented to build the driver's cognitive model the driver's signs cognitive behavioral model; Fourthly, the driving performance impairment and its main cause were identified based on driving behavior and decision-making output from the model. The traffic safety improvement measures were proposed from the aspects of signs designing and driving behavior intervention. It could complement and improve the existing traffic safety and driving behavior theories, then provide support for the analysis and effective prevention of mechanism of an accident in the progress of road signs reading.