Motional Ad LLC

Aptiv Technologies Limited

Yifan Yang

Junqing Wei

Guchan Ozbilgin

Wenda Xu

Jarrod M Snider

Yimu Wang

Eric Wolff

Scott D Pendleton

Hsun-Hsien Chang

Philipp Robbel

Maurilio Di Cicco

Noam Weinstein

Giancarlo Baldan

Alok Sharma

Matthias Sapuan

Akshay Bhagat

David Butterworth

Andrew J Eick

Mauro Aguiar

Bishwamoy Sinha Roy

Among other things, techniques are described for implementing occlusion representations over road features. In general, one innovative aspect of the subject matter described in this specification can be embodied in methods that include: obtaining area information of at least one area of interest for a vehicle, identifying occlusion data associated with the at least one area of interest, determining occlusion information associated with the at least one area of interest based on the area information and the occlusion data, providing the occlusion information for planning a route for the vehicle, and operating the vehicle in accordance with the planned route. The occlusion data includes data associated with the occlusion information, and the occlusion information has a smaller data size than the occlusion data.

Systems and methods for implementing occlusion representations over road features

Among other things, we describe systems and method for validating sensor calibration. For validating calibration of a system of sensors having several types of sensors, an object may be configured to have a substantially reflective portion such that the sensors can isolate the substantially reflective portion, and their sensor data can be compared to determine, if the detected locations of the substantially reflective portion by each sensor are aligned. For calibrating a system of sensors, an object having known calibration features can be used and detected by each sensor, and the detected data can be compared to known calibration data associated with the object to determine if each sensor is correctly calibrated.

Systems and methods for validating sensor calibration

A sensor data fusion system for a vehicle with multiple sensors includes a first-sensor, a second-sensor, and a controller-circuit. The first-sensor is configured to output a first-frame of data and a subsequent-frame of data indicative of objects present in a first-field-of-view. The first-frame is characterized by a first-time-stamp, the subsequent-frame of data characterized by a subsequent-time-stamp different from the first-time-stamp. The second-sensor is configured to output a second-frame of data indicative of objects present in a second-field-of-view that overlaps the first-field-of-view. The second-frame is characterized by a second-time-stamp temporally located between the first-time-stamp and the subsequent-time-stamp. The controller-circuit is configured to synthesize an interpolated-frame from the first-frame and the subsequent-frame. The interpolated-frame is characterized by an interpolated-time-stamp that corresponds to the second-time-stamp. The controller-circuit fuses the interpolated-frame with the second-frame to provide a fused-frame of data characterized by the interpolated-time-stamp, and operates the host-vehicle in accordance with the fused-frame.

Data fusion system for a vehicle equipped with unsynchronized perception sensors

A system includes a tracking system, a controller-circuit, and a device. The tracking system is configured to detect and track an object, and includes one or more of a computer vision system, a radar system, and a LIDAR system. The controller-circuit is disposed in a host vehicle, and is configured to receive detection signals from the tracking system, process the detection signals, determine, whether an object is detected based on the processed detecting signals, and in accordance with a determination that an object is detected, output command signals. The device is adapted to be mounted to the host vehicle, and is configured to receive the command signals and thereby provide a dynamic visual indication adapted to change in accordance with orientation changes between the host vehicle and the object. The dynamic visual indication is viewable from outside of the host vehicle.

Dynamic object detection indicator system for an automated vehicle

A vehicle perception sensor adjustment system includes a perception-sensor, a digital-map, and controller-circuit. The perception-sensor is configured to detect an object proximate to a host-vehicle. The perception-sensor is characterized as having a field-of-view that is adjustable. The digital-map indicates a contour of a roadway traveled by the host-vehicle. The controller-circuit in communication with the perception-sensor and the digital-map. The controller-circuit determines the field-of-view of the perception-sensor in accordance with the contour of the roadway indicated by the digital-map, and outputs a control-signal to the perception-sensor that adjusts the field-of-view of the perception-sensor.

Vehicle sensor configuration based on map data

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Pittsburgh, PA, United States of America

Yifan Yang