원문정보
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
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
