원문정보
초록
영어
The driver takes leading part in the complex model of "human-vehicle-road-environment". The driving behavior has the characteristics of randomness, impulsivity and autonomy etc. which make it difficult to study the driver's driving behavior directly. Monitoring vehicle attitude is an important element of proactive safety management of public transport vehicles. This paper constructs a data acquisition system by using an InvenSense's 6-Axis inertial measurement unit (IMU) as the center of this system, which can sense the vehicle attitude information to make up for the lack of driver senses, and then builds fuzzy synthetical evaluation model which is combined with ISO 2631-1:1997/Amd 1:2010 standard. Finally, prediction of the driver's driving behavior in transient term has been established with Elman neural network method.
목차
1. Introduction
2. The Evaluation of the Driver’s Bad Driving Behavior
2.1. The Establishment of ISO 2631-1:1997/AMD 1:2010 Standard Algorithms
2.2. Fuzzy Synthetic Evaluation Model
3. The Moving Vehicle Attitude Prediction by Elman Neural Network
3.1. The Learning Algorithm of Elman Neural Network
3.2. The Application of Elman Neural Network in Moving Vehicle Attitude Prediction
3.3. Prediction Results and Analysis
4. Conclusions
References