Vehicle state prediction in real time risk assessments

摘要

A driver assistance system takes as input a number of different types of vehicle environment inputs including positions of objects in the vehicle's environment. The system identifies possible outcomes that may occur as a result of the positions of the objects in the environment. The possible outcomes include predicted positions for the objects involved in each outcome. The system uses the inputs to determine a likelihood of occurrence of each of the possible outcomes. The system also uses the inputs to determine a current risk value for objects as well as predicted risk values for objects for the possible outcomes. A total risk value can be determined by aggregating the current and predicted risk values of an object weighted by the likelihood of occurrence. Total risk values for objects can be used to determine how the driver assistance system responds to the inputs.

主权项

1. A computer based method comprising:
receiving a plurality of vehicle environment inputs, the inputs comprising a current position for each of a plurality of objects located around a vehicle; determining, based on the inputs, a possible outcome involving the plurality of objects, the possible outcome comprising a predicted position for each of the involved objects; determining a numerical likelihood of occurrence of the possible outcome based on the inputs; determining, for each of the involved objects, a current risk value for the object based on the current position of the object, and a predicted risk value for the object based on the predicted position of the object; determining, for each of the involved objects, a total risk value based on the current risk value and based on the predicted risk value weighted by the numerical likelihood of occurrence; and controlling a driver assistance system of the vehicle based on the total risk values of the involved objects; wherein determining the numerical likelihood of occurrence of the possible outcome comprises: determining a plurality of memberships by the inputs in a plurality of input membership functions; combining the memberships into a plurality of permutations of the input membership functions; mapping the permutations to a plurality of outcome membership functions; aggregating the outcome membership functions;determining the numerical likelihood of occurrence based on the aggregation.