Abstract: In one embodiment, a method is provided. The method includes storing a set of training data. One or more machine learning models are trained based on the set of training data. The method also includes receiving, from a computing device, a request to access the set of training data. The method further includes determining whether the computing device is allowed to access the set of training data. In response to determining that the computing device is allowed to access the set of training data, the method includes transmitting a training token to the computing device. The training token grants a training environment with access to the set of training data for a period of time.

Abstract: A system and method are provided for observing conditions in an environment around a transportation vehicle and adjusting operation of the transportation vehicle in response to the observed conditions. The temperatures of features in the environment can be determined to compensate for varying conditions in the environment in operating the transportation vehicle.

Abstract: A computing system comprises a data storage and at least one processor communicatively coupled to the data storage. The at least one processor is configured to execute program instructions to cause the system to perform the following steps. A deep neural network (“DNN”) model is trained using training data. Next, additional scenes are determined based on the DNN model and the training data. The determined scenes are generated, and then used to augment the training dataset. The DNN model is then retrained using the augmented training dataset and stored in a data storage for deployment.

Abstract: In one embodiment, a method includes obtaining candidate data generated by a vehicle. The candidate data comprises a subset of sensor data identified based on a set of neural network models executing on the vehicle. The method also includes determining whether the candidate data can be associated with one or more categories of a set of categories for training data based on a set of categorization models. The method further includes associating the candidate data with the first category in response to determining that the candidate data can be associated with at a first category of the set of categories. The method further includes determining whether the candidate data can be associated with a second category. The set of categories lacks the second category. The method further includes including the second category in the set of categories in response to determining that the candidate data can be associated with the second category.

Abstract: A vehicle attachment for guiding a vehicle includes a magnetic tape sensor, at least one sensor, a controller, at least one coupling device for attachment to the vehicle, and a vehicle interface system. The magnetic tape sensor is configured to detect a path. The at least one sensor can detect whether there are any obstructions along the path. The controller is configured to steer the vehicle along the predefined path and to adjust the speed of the vehicle to avoid coming in contact with any obstructions. The vehicle interface system is configured to communicatively couple the controller to at least one electronic control unit of the vehicle.

Abstract: In one embodiment, a method is provided. The method includes receiving sensor data generated by a set of vehicles. The method also includes performing a first set of processing operations on the sensor data. The method further includes providing an exploration interface configured to allow one or more of browsing, searching, and visualization of the sensor data. The method further includes selecting a subset of the sensor data. The method further includes performing a second set of processing operations on the subset of the sensor data. The method further includes provisioning one or more of computational resources and storage resources for developing an autonomous vehicle (AV) model based on the subset of the sensor data.

Abstract: The lifting platform (10) has at least two lateral pillars (12, 14, 33). Each pillar has height-changeable, pivotable arms (13, 34, 44) that are displaceable telescopically in length. An end of each arm has a decoupling device with a receptacle (31, 41) for supporting an object. A carrying device (11, 50) has receiving points corresponding to the number of the receptacles (31, 41). The lifting platform and the carrying device are positioned with respect to each other without impairing an object resting on the at least one receptacle. The at least one receptacle (31, 41) is placed onto the at least one receiving point, and the carrying device (11, 50) together with the transferred at least one receptacle (31, 41) and an object thereon is removed from a region of the lifting platform (10).

Abstract: Technologies and techniques for determining locations of a plurality of markers on a vehicle in three-dimensional space. The markers may be configured as optical or radio markers, where a sensor determines the locations of each of the plurality of markers, or a shape formed by the markers collectively. The locations of each of the plurality of markers or shape is then compared to a template to determine a match. The match identifies a vehicle having vehicle data that includes locations of vehicle components and/or vehicle performance characteristics. The vehicle data is then used to generate control signals for controlling a control device that may be associated with a robotic apparatus, a vehicle computer system and/or drone operating system.

Abstract: Devices, systems, and methodologies for providing a comfort system of a transportation vehicle include capturing and assessing movement data of a user. The movement data can include movement data captured upon the user's approach to the transportation vehicle.

Abstract: Systems, devices and methodologies for generating a vehicle identification hash value and verifying the integrity of the vehicle. The vehicle identification hash value is generated based on hashes provided by each vehicle component. The generated overall vehicle identification hash value may be dynamic and reflects changes that occur to the vehicle at the component level.

Abstract: A system and methodologies for neuromorphic (NM) vision simulate conventional analog NM system functionality and generate digital NM image data that facilitate improved object detection, classification, and tracking.

Abstract: A system, device and method for wireless device localization using a differential evolution algorithm in a continuous trilateration process.

Abstract: Systems, components, and methodologies are provided for improvements in operation of automotive vehicles by enabling monitoring analysis and reaction to subtle sources of information that aid in prediction and response of vehicle control systems across a range of automation levels. Such systems, components, and methodologies include wheel-turn detection equipment for detecting a wheel angle of another vehicle to trigger a vehicle control system to perform an operation based on the detected wheel angle of the other vehicle.

Abstract: A system and methodologies for neuromorphic vision simulate conventional analog NM system functionality and generate digital NM image data that facilitate improved object detection, classification, and tracking.

Abstract: A system and methodologies for neuromorphic vision simulate conventional analog NM system functionality and generate digital NM image data that facilitate improved object detection, classification, and tracking so as to detect and predict movement of a vehicle occupant.

Abstract: A system and method are provided for controlling traffic signals using virtual induction loops. The system allows bidirectional communication between a traffic signal controller and a vehicle so that the controller can send map data to the vehicle and the vehicle can send a recall message to the controller, requesting to be served by the controller at an approaching traffic signal.

Abstract: A system and methodologies for neuromorphic vision simulate conventional analog NM system functionality and generate digital NM image data that facilitate improved object detection, classification, and tracking.

Abstract: A system and methodologies for neuromorphic (NM) vision simulate conventional analog NM system functionality and generate digital NM image data that facilitate improved object detection, classification, and tracking.

Abstract: Systems, components, and methodologies are provided for improvements in operation of automotive vehicles by enabling emulation of traffic signal operation by genertic algorithms, providing tunable solutions for efficient and safe operation.

Abstract: A system and methodologies for neuromorphic vision simulate conventional analog NM system functionality and generate digital NM image data that facilitate improved object detection, classification, and tracking.