Patent Document ID: 9969388
Application ID: 14603990
Patent Status: 1

Claim One:
1. A method for computationally predicting future movement behavior of a target object, comprising the steps of: producing sensor data by at least one sensor physically sensing the environment of a host vehicle; computing a plurality of movement behavior alternatives of the target object sensed by the sensors, by predicting movement behaviors of the target object applying a context based prediction step using, for at least one of the plurality of movement behavior alternatives, at least one of indirect indicator or indicator combinations derived from sensor data, wherein in said context based prediction step a probability that the target object will execute a movement behavior at a time is estimated; estimating a future position of the target object; and outputting a signal representing the estimated future position, wherein in the context based prediction step, at least one history indicator is used, wherein the at least one history indicator being calculated for a current point in time using at least one indicator value of the indirect indicator at a past point in time, wherein the past point in time is defined by an observed previous behavior of the target vehicle or an occurrence of a particular situation in the past, and wherein the indicator value depending on a time difference between the current point in time and the past point in time, wherein the indicator value is a minimum value when the time difference is below a first threshold, the indicator value is a maximum value when the time difference exceeds a second threshold, and wherein the indicator value increases from the minimum value to the maximum value when the time difference ranges from the first threshold to the second threshold, or wherein the indicator value is the maximum value when the time difference is below the first threshold, the indicator value is the minimum value when the time difference exceeds the second threshold, and wherein the indicator value decreases from the maximum value to the minimum value when the time difference ranges from the first threshold to the second threshold.