Multi-hypothesis object tracking for automated driving systems

A method for multi-hypothesis object tracking, the method comprising:

• receiving environment information;
• generating, with an electronic processor, pseudo-measurement data by generating a first measurement model hypothesis based on a first assumption that the object is of a first object type and generating a second measurement model based on a second assumption that the object is of a second object type different from the first object type;
• generating, based on the environment information and the pseudo-measurement data, a set of association hypotheses for an object within an environment surrounding a vehicle;
• determining, with the electronic processor, an object state for the object based on the set of association hypotheses;
• and
• controlling the vehicle based on the determined object state.

A non-transitory, computer-readable medium storing instructions that, when executed by an electronic processor, perform a set of functions, the set of functions comprising:

• receiving, from at least one sensor, environment information of a field of view, the field of view including an object;
• generating pseudo-measurement data by generating a first measurement model hypothesis based on a first assumption that the object is of a first object type and generating a second measurement model based on a second assumption that the object is of a second object type different from the first object type;
• generating, based on the environment information and the pseudo-measurement data, a set of association hypotheses for the object within the field of view;
• determining an object state for the object based on the set of association hypotheses;
• determining a vehicle maneuver based on the determined object state, and
• controlling a vehicle based on the vehicle maneuver.