Motional Ad LLC

Nutonomy Inc.

Aravindkumar Vijayalingam

Baoxing Qin

Scott D Pendleton

Abhimanyu Singh

Daniele De Francesco

Ruben Strenzke

Provided are methods for thermal sensor data vehicle perception, which can include obtaining thermal sensor data, obtaining non-thermal sensor data, and determining, based on the thermal sensor data and the non-thermal sensor data, a perception parameter indicative of an object. Some methods described also include generating a trajectory for an autonomous vehicle. Systems and computer program products are also provided.

Thermal sensor data vehicle perception

Techniques for autonomous vehicle operation using acoustic modalities include using one or more acoustic sensors of a vehicle to receive acoustic waves from one or more objects. The acoustic waves have multiple wavelengths. The acoustic waves are clustered into one or more acoustic clusters based on the plurality of wavelengths. A particular acoustic cluster of the one or more acoustic clusters is selected based on signal processing of the one or more acoustic clusters. A particular object is associated with the particular acoustic cluster. An acoustic fingerprint of the particular object is generated based on the particular acoustic cluster. Characteristics of the particular object are determined based on the acoustic fingerprint of the particular object. A control circuit of the vehicle is used to operate the vehicle to avoid a collision with the particular object based on the characteristics of the particular object.

Autonomous vehicle operation using acoustic modalities

Among other things, techniques are described for improving the trajectory estimates for an object in an environment. The technique includes receiving, by at least one processor, information indicating a presence of an object operating in an environment; determining, by the at least one processor, a trajectory of the object, the trajectory including at least a position, a speed, and a direction of travel of the object; determining, by the at least one processor, an expected route of the object, wherein the expected route is pre-planned and includes an expected future position of the object at a future time; comparing the trajectory of the object to the expected route of the object; and in accordance with the comparison that the trajectory of the object is consistent with the expected route of the object, updating the trajectory of the object based on the expected route of the object.

Trajectory planning of vehicles using route information

Among other things, one or more travel signals are identified by analyzing one or more images and data from sensors, classifying candidate travel signals into zero, one or more true and relevant travel signals, and estimating a signal state of the classified travel signals.

Automatically perceiving travel signals

Among other things, we describe techniques for traffic light estimation using range sensors. A planning circuit of a vehicle traveling on a first drivable region that forms an intersection with a second drivable region receives information sensed by a range sensor of the vehicle. The information represents a movement state of an object through the intersection. A traffic signal at the intersection controls movement of objects through the intersection. The planning circuit determines a state of the traffic signal at the intersection based, in part, on the received information. A control circuit controls an operation of the vehicle based, in part, on the state of the traffic signal at the intersection.

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Singapore, Singapore

Aravindkumar Vijayalingam