Research Of Vehicle Driving Fatigue Recognition System

With the rapid development of modern transportation, road traffic accidents caused by vehicle driving fatigue have also grown dramatically, which is a serious threat to people's lives and property. The rapid development of Intelligent Transportation Systems (ITS) technology provides the road traffic safety issues a new way of thinking. Advanced information technology, communication technology, control technology, sensor technology and system synthesis technology are applied to road traffic safety areas, especially the research of driving fatigue. ITS provides useful technical support to reduce road traffic accidents caused by driving fatigue.After the study of driving fatigue research conditions, this paper summarize two different driving fatigue recognition methods, they are separately based on driver behavior feature and vehicle state characteristics.In this study, the vehicle driving fatigue recognition system is based on driving behavior and vehicle driving status, the specific content of the paper are described as follows:(1) The domestic and international recognition methods of driving fatigue were introduced and analyzed. Of vehicle driving fatigue problems, this paper research on the basis of driving behavior and vehicle driving status. The interaction between the transport system factors were analyzed in detail, and the recognition principle of system were expounded as well. Finally, the steering, throttle, clutch, brake, speed and acceleration information are select as the feature index to recognize driving fatigue.(2)According to the thinking of modular design, the parts of hardware and software were designed in this paper. Secondly, main control module, the signal collecting module, the voltage transform module, the serial communication module and alarm module were designed. And then the problems need pay attention to were described, which including circuit layout wiring, anti-interference issues and anti-static issues. Finally, design of software were described.(3)The relevant information of vehicle driving fatigue recognition were collected from the vehicle driving simulator. The paper give a brief description of analysis of the data, driving fatigue recognition algorithm were designed. There are two types of sample data, one is 100 groups of driving fatigue recognition features data and driving state data, the other is 100 groups of principal component features and driving state data. Two types of data were analyzed through BP neural network and RBF neural network. The results show that, no matter driving fatigue recognition features and principal component features could be used to identify driving state. The effect of BP neural network is better than RBF neural network; principal component extraction does not affect the accuracy of driving fatigue recognition, and could reduce the complexity of the data and improve the efficiency.