Motional Ad LLC

Emilio Frazzoli

Eric Wolff

Scott D Pendleton

Hsun-Hsien Chang

Paul Schmitt

Kostyantyn Slutskyy

Andrea Censi

Elena Corina Grigore

Tung Minh Phan

Freddy Boulton

Cristhian Guillermo Lizarazo Jimenez

Juraj Kabzan

Luke Fletcher

Among other things, planning a motion of a machine having moving capabilities is based on strategic guidelines derived from various basic principles, such as laws, ethics, preferences, driving experiences, and road environments.

Planning autonomous motion

Among other things, techniques are described for expressive vehicle systems. These techniques may include obtaining, with at least one processor, data associated with an environment, the environment comprising a vehicle and at least one object; determining an expressive maneuver including a deceleration of the vehicle such that the vehicle stops at least a first distance away from the at least one object and the vehicle reaches a peak deceleration when the vehicle is a second distance away from the at least one object; generating data associated with control of the vehicle based on the deceleration associated with the expressive maneuver; and transmitting the data associated with the control of the vehicle to cause the vehicle to decelerate based on the deceleration associated with the expressive maneuver.

Communicating vehicle information to pedestrians

Multiple trajectories for a vehicle are generated based on a road segment. Sensor data is received from at least one sensor. The vehicle is traveling the road segment in accordance with a first trajectory of the multiple trajectories. A potential collision is predicted between the vehicle and an object based on the sensor data and the first trajectory. A set of constraints is determined to avoid the potential collision. The set of constraints is determined based on the sensor data. A maneuver is determined for the vehicle by superimposing each constraint of the set of constraints on each other constraint of the set of constraints. The maneuver includes a second trajectory independent of the multiple trajectories. Instructions are transmitted to a control circuit of the vehicle to override the first trajectory and traverse the road segment according to the second trajectory to perform the maneuver.

Vehicle operation using maneuver generation

Among other things, techniques are described for predicting how an agent (e.g., a vehicle, bicycle, pedestrian, etc.) will move in an environment based on prior movement, the road network, the surrounding objects and/or other relevant environmental factors. One trajectory prediction technique involves generating a probability map for an agent's movement. Another trajectory prediction technique involves generating a trajectory lattice, for an agent's movement. In addition, a different trajectory prediction technique involves multi-modal regression where a classifier (e.g., a neural network) is trained to classify the probability of a number of (learned) modes such that each model produces a trajectory based on the current input.

Trajectory prediction from precomputed or dynamically generated bank of trajectories

Growing community of inventors

Newton, MA, United States of America

Emilio Frazzoli