Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

The present invention relates to determination of a state of a vehicle on a road portion. The vehicle includes an Automated Driving System (ADS) feature. At first, map data associated with the road portion, positioning data indicating a pose of the vehicle on the road, and sensor data of the vehicle are obtained. Then, a plurality of filters for the road portion are initialized. Further, one or more sensor data point(s) in the obtained sensor data is associated to a corresponding map-element of the obtained map data to determine one or more normalized similarity score(s). Now, based on the determined one or more normalized similarity score(s), one or more multivariate time-series data are also determined and provided as input to a trained machine-learning algorithm. Then, one of the initialized filters is selected by the machine learning algorithm to indicate a current state of the vehicle on the road portion.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

Systems and methods for predicting anomalies in a wheel system of a semi-trailer truck. One example system includes: a vibration sensor positioned to sense vibrations of the wheel system and an electronic processor communicatively coupled to the vibration sensor. The electronic processor is configured to determine a velocity profile of the semi-trailer truck; obtain a vibration measurement; determine, from the vibration measurement, a classified vibration level; determine whether the classified vibration level is indicative of an anomaly; identify, based on whether the classified vibration level is indicative of the anomaly and both the velocity profile and a reference classified vibration level, an anomaly existing within either or both of the semi-trailer truck wheel system or the road; and perform a mitigation action in response to identifying the anomaly.

Aspects of the present invention relate to a speed control system (15) for a vehicle (10), to a method and to a vehicle (10). The system causes the vehicle (10) to drive at a target speed value. The speed control system (15) uses a pitch rate signal indicative of a rate of change of pitch of a vehicle (10) and a driving surface gradient signal indicative of a gradient of a driving surface upon which the vehicle (10) is being driven to determine if the vehicle is cresting. The determination that cresting is occurring depends on the rate of change of pitch exceeding a predetermined value; and the gradient value of the driving surface being below a predetermined value. The speed control system (15) outputs a speed reduction signal to reduce the speed of the vehicle when the vehicle is cresting.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

A sensor calibration system periodically receives scene data from a detector in a calibration scene. The calibration scene includes calibration targets. The sensor calibration system generates a calibration map based on the scene data. The calibration map is a virtual representation of the calibration scene and includes features of the calibration targets that can be used as ground truth features for calibrating AV sensors. The sensor calibration system can periodically update the calibration map. For instance, the sensor calibration system receives the scene data at a predetermined frequency and updates the calibration map every time it receives new scene data. The predetermined frequency may be a frequency of the detector completing a full scan of the calibration scene. The sensor calibration system provides a latest version of the calibration map for being used by an AV to calibrate a sensor on the AV 110.

Out of two areas divided by a virtual line passing through the center of gravity position in the front-back direction of a vehicle, a second acceleration sensor is arranged in an area different from the area where a first acceleration sensor is arranged. Out of two areas divided by a virtual line passing through the center of gravity position in the vehicle width direction, the third acceleration sensor is arranged in an area different from the area where the first acceleration sensor is arranged. At least one of the following conditions is satisfied: the first condition where the third acceleration sensor is located between the first acceleration sensor and the second acceleration sensor in the vehicle width direction; and the second condition where the second acceleration sensor is located between the first acceleration sensor and the third acceleration sensor in the front-back direction of the vehicle.

The present disclosure generally relates to sensor calibration and more specifically, to sensor calibration using weather data. In some aspects, the present disclosure provides a process for receiving a set of weather data from a weather measurement station disposed within a calibration environment, determining if a predetermined weather condition is indicated by the set of weather data, and collecting, using one or more AV sensors, a set of sensor data within the calibration environment, if the predetermined weather condition is indicated by the set of weather data. Systems and machine-readable media are also provided.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.