Predicting and responding to cut in vehicles and altruistic responses

A host vehicle comprising:

• at least one image capture device;
• and
• a vehicle navigation system configured to:
• receive image data captured by the at least one image capture device, the image data being representative of an environment of the host vehicle;
• identify, based on analysis of the image data, a target vehicle traveling in a lane adjacent to a lane in which the host vehicle is traveling;
• identify, based on analysis of the image data, one or more situational characteristics of the target vehicle indicating the target vehicle would benefit from a change in a navigational state of the host vehicle, wherein identifying the one or more situational characteristics of the target vehicle comprises:
• tracking a representation of the target vehicle across multiple image frames, and
• generating measurements of the target vehicle using one or more time-based observations, and
• wherein the situational characteristics of the target vehicle include:
• an indication that the target vehicle is traveling at a first speed behind an additional vehicle in the lane adjacent to the lane in which the host vehicle is traveling, and
• an indication that the additional vehicle is traveling at a second speed, wherein the second speed is lower than the first speed;
• determine, based on the first speed of the first target vehicle and the second speed of the additional target vehicle, that the target vehicle would benefit from a change in a navigational state of the host vehicle to allow a cut-in by the target vehicle into the lane in which the host vehicle is traveling;
• and
• cause the change in the navigational state of the host vehicle to allow the cut-in by the target vehicle.

At least one non-transitory machine-readable medium including instructions that, when executed by circuitry of a vehicle component for a host vehicle, cause the circuitry to perform operations comprising:

• receiving image data captured by at least one image capture device of the host vehicle, the image data being representative of an environment of the host vehicle;
• identifying, based on analysis of the image data, a target vehicle traveling in a lane adjacent to a lane in which the host vehicle is traveling;
• identifying, based on analysis of the image data, one or more situational characteristics of the target vehicle indicating the target vehicle would benefit from a change in a navigational state of the host vehicle, wherein identifying the one or more situational characteristics of the target vehicle comprises:
• tracking a representation of the target vehicle across multiple image frames, and
• generating measurements of the target vehicle using one or more time-based observations, and
• wherein the situational characteristics of the target vehicle include:
• an indication that the target vehicle is traveling at a first speed behind an additional vehicle in the lane adjacent to the lane in which the host vehicle is traveling, and
• an indication that the additional vehicle is traveling at a second speed, wherein the second speed is lower than the first speed;
• determining, based on the first speed of the first target vehicle and the second speed of the additional target vehicle, that the target vehicle would benefit from a change in a navigational state of the host vehicle to allow a cut-in by the target vehicle into the lane in which the host vehicle is traveling;
• and
• cause the change in the navigational state of the host vehicle to allow the cut-in by the target vehicle.