Earticle

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

Abstract
 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

키워드

저자

• Huaikun Xiang [ Shenzhen Polytechnic, Shenzhen 518055, Guangdong, China ]
• Shaopeng Yang [ Harbin Institute of Technology, Harbin 150001, heilongjiang, China The co-first author is Shaopeng Yang Correspondence should be addressed to Shaoyun Ren; ]
• Shi An [ Harbin Institute of Technology, Harbin 150001, heilongjiang, China The co-first author is Shaopeng Yang Correspondence should be addressed to Shaoyun Ren; ]
• Shaoyun Ren [ Shenzhen Polytechnic, Shenzhen 518055, Guangdong, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Security and Its Applications

• 간기

  격월간

• pISSN

  1738-9976

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605