Mercedes-benz Group Ag

Christopher Monaco

Manuel Schier

Anne Kickton

Yooseong Kim

Subject matter disclosed herein may relate to systems, devices and/or processes for monitoring and/or evaluating vehicle pose integrity for use with an autonomous driving controller. A system may include memory, the memory comprising one or more memory devices and a processor coupled to the one or more memory devices, the processor configured to access, from the one or more memory devices, sensor measurements generated by one or more sensors mounted in a vehicle. The system may additionally observe one or more semantic classes to one or more physical entities based on the generated sensor measurements and extract one or more semantically-labeled map parameters from an electronic map the system may additionally determine a correlation between the one or more observed semantic classes and one or more expected classes extracted from the semantically-labeled map parameters.

Evaluating integrity of vehicle pose estimates via semantic labels

Methods and computing systems for mitigating motion sickness are described. A computing system includes a control circuit to receive data indicating an inertial state of a vehicle, simulate a fluid based on the data indicating the inertial state of the vehicle, and output command instructions to cause the simulated fluid to be visualized within an interior of the vehicle using one or more lighting elements from among a plurality of activatable lighting elements of the vehicle.

Method and computing system for mitigating motion sickness in a vehicle

Methods and systems for improving the charging of battery electric vehicles (BEVs) using solar irradiance. For example, a computing system may be configured to obtain sensor data from a plurality of vehicles, where the sensor data is indicative of sensor measurement data acquired by a perception sensor of the respective vehicle, a time the sensor measurement data was acquired, and a pose of the vehicle. The computing system may be configured to, based on the sensor data from the plurality of vehicles, determine a plurality of solar irradiance levels for a plurality of locations within a geographic area. The computing system may be configured to generate a map layer, the map layer being indicative of a respective solar irradiance level for each of the plurality of locations. The computing system may be configured to output the map layer for integration into map data associated with the geographic area.

Creation of sunlight occupancy grid map for electric vehicles

A system can perform a method that includes receiving sensor data from one or more sensors. The system can execute a sample-based estimator on the sensor data. The sample-based estimator optimizes a probability distribution dilation of the sensor data based on a minimum measurement uncertainty value to minimize aliasing in the sample-based estimator.

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Sunnyvale, CA, United States of America

Christopher Monaco