Potential collision warning system based on road user intent prediction

An apparatus comprising:

• a memory to store a first observed trajectory and a second observed trajectory of a pedestrian, the first observed trajectory comprising a plurality of observed locations of the pedestrian over a first plurality of timesteps, the second observed trajectory comprising a plurality of observed locations of the pedestrian over a second plurality of timesteps, wherein the second plurality of timesteps includes the first plurality of timesteps and at least one additional subsequent timestep;
• and
• one or more processors, at least one of the one or more processors coupled to the memory, the one or more processors comprising circuitry, the one or more processors to:
• generate a predicted trajectory of the pedestrian, the predicted trajectory comprising a plurality of predicted locations of the pedestrian over the second plurality of timesteps and over a third plurality of timesteps occurring after the second plurality of timesteps;
• determine a first likelihood of the predicted trajectory based on a comparison of the plurality of predicted locations of the pedestrian over the first plurality of timesteps and the plurality of observed locations of the pedestrian over the first plurality of timesteps;
• and
• determine a second likelihood of the predicted trajectory based on a comparison of the plurality of predicted locations of the pedestrian over the second plurality of timesteps and the plurality of observed locations of the pedestrian over the second plurality of timesteps.

A method comprising:

• accessing a first observed trajectory and a second observed trajectory of a pedestrian, the first observed trajectory comprising a plurality of observed locations of the pedestrian over a first plurality of timesteps, the second observed trajectory comprising a plurality of observed locations of the pedestrian over a second plurality of timesteps, wherein the second plurality of timesteps includes the first plurality of timesteps and at least one additional subsequent timestep;
• generating a predicted trajectory of the pedestrian, the predicted trajectory comprising a plurality of predicted locations of the pedestrian over the second plurality of timesteps and over a third plurality of timesteps occurring after the second plurality of timesteps;
• determining a first likelihood of the predicted trajectory based on a comparison of the plurality of predicted locations of the pedestrian over the first plurality of timesteps and the plurality of observed locations of the pedestrian over the first plurality of timesteps;
• and
• determining a second likelihood of the predicted trajectory based on a comparison of the plurality of predicted locations of the pedestrian over the second plurality of timesteps and the plurality of observed locations of the pedestrian over the second plurality of timesteps.

At least one non-transitory machine-readable storage medium having instructions stored thereon, the instructions when executed by a machine to cause the machine to:

• access a first observed trajectory and a second observed trajectory of a pedestrian, the first observed trajectory comprising a plurality of observed locations of the pedestrian over a first plurality of timesteps, the second observed trajectory comprising a plurality of observed locations of the pedestrian over a second plurality of timesteps, wherein the second plurality of timesteps includes the first plurality of timesteps and at least one additional subsequent timestep;
• generate a predicted trajectory of the pedestrian, the predicted trajectory comprising a plurality of predicted locations of the pedestrian over the second plurality of timesteps and over a third plurality of timesteps occurring after the second plurality of timesteps;
• determine a first likelihood of the predicted trajectory based on a comparison of the plurality of predicted locations of the pedestrian over the first plurality of timesteps and the plurality of observed locations of the pedestrian over the first plurality of timesteps;
• and
• determine a second likelihood of the predicted trajectory based on a comparison of the plurality of predicted locations of the pedestrian over the second plurality of timesteps and the plurality of observed locations of the pedestrian over the second plurality of timesteps.