Algorithm of Traffic State Probability Forecast Based on Logistic Regression


According to the stochastic property and complexity of the traffic flow evolution on the urban road and the uncertainty of traffic state discrimination, and based on the analysis of the mapping relationship between traffic state and traffic flow parameters, an algorithm of Logistic regression for traffic state probability forecast is put forward. The proposed algorithm explores the function relationship of traffic state and the influencing factors by means of Logistic regression and thus gives the probability prediction of the traffic state of the next time period. Finally, according to the proposed algorithm, the grading traffic state probability forecast experiments of different time periods is carried out using the field traffic flow data. The results of independent sample test indicate that the model has a finer precision and stability.

  • Abstract
  • Keywords
  • Introduction
  • Problem Description and Research Thinking
  • Model Construction Of Traffic State Probability Forecast
  • Experiments Of Traffic State Probability Forecast
  • Conclusion
  • References

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