The accurate prediction for the travel time can improve bus operation efficiency. The improvement of bus service level and enhancement of bus trip can relieve the urban traffic problems. To predict bus travel time between adjacent signalized intersections, BP neural network model was used. Factors which influence bus travel time were considered as the input of the network model, and bus travel time was used as the output. Bus route No. 3 in Nanjing was chosen as a case study. The results verify model's feasibility and indicates that the presented model has certain practical values.
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