To solve the optimal path problem of the traffic network, an improved travel time estimation model was proposed, and an optimal path algorithm based on this model was designed. The travel time estimation model was improved on the basis of the segment truncated quadratic velocity trajectory model by replacing the velocity measured at the same departure moment with the arrival velocity of the road segment nodes, and the travel time was estimated by constructing a velocity trajectory that is continuous in time and space. The optimal path algo-rithm based on travel time estimation firstly solved K shortest paths based on Yen′s KSP algorithm with road section distance as impedance, then estimated the travel time of K shortest paths by the improved travel time es-timation model respectively, and finally selected the optimal path with travel time as cost. The validity and superiority of the model and algorithm were verified by numerical experiments of Sioux falls network. The experimental results show that the improved segmented truncated quadratic speed trajectory model improves the accuracy by an average of 65% compared with the original model and the optimal path results based on the proposed al-gorithm can reduce the number of intersections the path passes through and shorten the total length of the opti-mal path. Moreover, the estimated results of the optimal path's travel time stay within 3% of the real value of MAPE. The results of this study may provide a theoretical basis for the optimal path method for traffic networks.