A Novel Algorithm with an Integrated Model for the Prediction of Sudden Trajectory Behaviors

This paper introduces a new algorithm with an integrated model for the prediction of sudden trajectory behaviors. The algorithm systematically introduces an integrated solution of multiple models to address the specific challenges of sudden trajectory behaviors for better prediction. The multiple models include the exponential growth reward-oriented model, the timing model, the reinforcement model, and the cyclical behavior model. The model list may be extended to cover more challenges later. Additional research may be conducted to explore the automation of prediction parameters and dataset storage for the best prediction accuracy of sudden trajectory behaviors.