Abstract
Travel time parameters obtained from road traffic sensors data play an important role in traffic management practice. In this paper, a travel time analysis and prediction model was established for urban road traffic sensors data based on the change point analysis algorithm and ARIMA model. Firstly, time series of travel time parameters were clustered by using change point mining algorithm after traffic sensors data preprocessing. Then, a travel time prediction model was established based on ARIMA model. Finally, the model was verified with high accuracy through simulation by using multiple sets of data and analysis of its practicability was done.
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