On freeway traffic density estimation for a jump Markov linear model based on Daganzo's cell transmission model

This paper deals with problem of the real-time freeway traffic density estimation/prediction for a jump Markov linear model based on Daganzo's cell transmission variant of the Lighthill-Whitham-Richards continuous macroscopic freeway model. To solve the problem we propose a particle-filtering-based estimation/prediction method. Its performance is illustrated on case studies involving a four-cell freeway segment. The case studies suggest that the proposed methodology can be used for real-time traffic density estimation/prediction. Possible pitfalls of our approach are also discussed.