Earticle

초록

영어

Urban road traffic state identification is a key link to realize the intelligent transportation based on the Internet of Vehicles, and accurately positioning vehicles is the foundation to realize the traffic state identification. Aiming at the problem that GPS has signal blind area in positioning vehicles, a vehicle positioning algorithm based on particle filter was proposed, it could improve the traditional algorithm on degradation and large amount of calculations; Based on vehicle positioning, an urban road traffic state identification algorithm based on fuzzy discrimination was proposed, it could comprehensively consider multiple factors’ influence on traffic state. The experiment results show that the improved particle filter algorithm’s mean squared error has increased about 55.437% compared with GPS method, and the traffic state identification algorithm can accurately identify the traffic state of the study area, it can prove that the urban road traffic state identification algorithm based on particle filter and fuzzy discrimination is feasible and effective.

목차

Abstract
 1. Introduction
 2. Vehicle Positioning Algorithm Based On Improved Particle Filter
  2.1. Vehicle Coordinates Calculation Based on TDOA
  2.2. Weighted Coordinates Calculation Based on RSSI
  2.3. Vehicle Positioning Algorithm Based On Improved Particle Filter
 3. Road Traffic State Identification Algorithm Based On Fuzzy Discrimination
  3.1. Traffic States and Evaluation Factors
  3.2. Subordinate Function and Weight
  3.3. Road Traffic State Identification Algorithm Based On Fuzzy Discrimination
 4. Simulation Experiment and Analysis
  4.1. Simulation Experiment and Analysis of the Vehicle Positioning Algorithm
  4.2. Simulation Experiment and Analysis of Traffic State Identification
 5. Conclusions
 Acknowledgements
 References

키워드

저자

• Guo Yanling [ College of Mechanical and Electrical Engineering, Northeast Forestry University, Harbin, China ]
• Liu Lichen [ College of Mechanical and Electrical Engineering, Northeast Forestry University, Harbin, China ]
• Gao Meng [ Information and Computer Engineering College, Northeast Forestry University, Harbin, China ]
• Gao Lewen [ China Mobile Communications Corporation Design Institute Co,. Ltd. of Heilongjiang Branch, Harbin, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Smart Home

• 간기

  격월간

• pISSN

  1975-4094

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605