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公开(公告)号：US12164367B2
公开(公告)日：2024-12-10
申请号：US17126148
申请日：2020-12-18
Applicant: Intel Corporation
Inventor： Rafael Rosales , Michael Paulitsch , David Israel González Aguirre , Florian Geissler , Ralf Graefe
IPC: G06F11/00 , G06F11/07 , G06F16/901 , G06N7/01
Abstract: A computer-implemented method may include obtaining, from a system using a middleware component of the system, run-time evidence of the system; applying the obtained run-time evidence to a Directed Acyclic Graph (DAG) Bayesian network to determine marginal probabilities for one or more nodes of the DAG Bayesian network, wherein the DAG Bayesian network comprises a plurality of nodes each representing states and faults of the system, wherein each node includes a parameterized conditional probability distribution, and wherein one or more of the nodes of the plurality of nodes specify a list of one or more safety goals and a safety value; determining which nodes representing faults have probabilities exceeding their specified safety value; and determining one or more risk mitigation techniques to activate for the determined nodes representing faults with probabilities exceeding their respective safety value.
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公开(公告)号：US12063511B2
公开(公告)日：2024-08-13
申请号：US17130631
申请日：2020-12-22
Applicant: Intel Corporation
Inventor： Florian Geissler , S M Iftekharul Alam , Yaser M. Fouad , Michael Paulitsch , Rafael Rosales , Kathiravetpillai Sivanesan , Kuilin Clark Chen
IPC: H04W12/104 , H04W4/40 , H04W12/00
CPC classification number: H04W12/104 , H04W4/40 , H04W12/009
Abstract: V2X trusted agents provide technical solutions for technical problems facing falsely reported locations of connected vehicles within V2X systems. These trusted agents (e.g., trusted members) may be used to detect an abrupt physical attenuation of a wireless signal and determine whether the attenuation was caused by signal occlusion caused by the presence of an untrusted vehicle or other untrusted object. When the untrusted vehicle is sending a message received by trusted agents, these temporary occlusions allow trusted members to collaboratively estimate the positions of untrusted vehicles in the shared network, and to detect misbehavior by associating the untrusted vehicle with reported positions. Trusted agents may also be used to pinpoint specific mobile targets. Information about one or more untrusted vehicles may be aggregated and distributed as a service.
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公开(公告)号：US12205460B2
公开(公告)日：2025-01-21
申请号：US17131900
申请日：2020-12-23
Applicant: Intel Corporation
Inventor： Ralf Graefe , Michael Paulitsch , Norbert Stoeffler
Abstract: A pedestrian route can be segmented into at least one pedestrian walking segment using location information of transportation resources. An estimated transit time for the pedestrian route can be determined as a function of an estimated transit time of the at least one pedestrian walking segment, an estimated wait time for the transportation resource to arrive at the user determined using received status real-time location and movement information of the transportation resource and the determined estimated transit time for the at least one pedestrian walking segment, and an estimated transit time for the transportation resource to transport the user.
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公开(公告)号：US20240369369A1
公开(公告)日：2024-11-07
申请号：US18572578
申请日：2021-09-23
Applicant: Intel Corporation
Inventor： Chien Chern Yew , Say Chuan Tan , Yang Peng , Devamekalai Nagasundaram , Florian Geissler , Michael Paulitsch , Ying Wei Liew
Abstract: Disclosed herein are embodiments of systems and methods for accessible vehicles (e.g., accessible autonomous vehicles). In an embodiment, a passenger-assistance system for a vehicle includes first circuitry, second circuitry, third circuitry, and fourth circuitry. The first circuitry is configured to identify an assistance type of a passenger of the vehicle. The second circuitry is configured to control one or more passenger-comfort controls of the vehicle based on the identified assistance type. The third circuitry is configured to generate a modified route for a ride for the passenger at least in part by modifying an initial route for the ride based on the identified assistance type. The fourth circuitry is conduct a pre-ride safety check and/or a pre-exit safety check based on the identified assistance type.
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5.发明申请公开(公告)号：US20220222927A1
公开(公告)日：2022-07-14
申请号：US17710770
申请日：2022-03-31
Applicant: Intel Corporation
Inventor： Rafael Rosales , Pablo Munoz , Neslihan Kose Cihangir , Michael Paulitsch
IPC: G06V10/776 , G06V10/764
Abstract: For example, an apparatus may include an input to receive Machine Learning (ML) model information corresponding to an ML model to process input information; and a processor to construct a multi-model ML architecture including a plurality of ML model variants based on the ML model, wherein the processor is configured to determine the plurality of ML model variants based on an attribution-based diversity metric corresponding to a model group including a first ML model variant and a second ML model variant, wherein the attribution-based diversity metric corresponding to the model group is based on a diversity between a first attribution scheme and a second attribution scheme, the first attribution scheme representing first portions of the input information attributing to an output of the first ML model variant, the second attribution scheme representing second portions of the input information attributing to an output of the second ML model variant.
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Patent Agency Ranking
公开(公告)号：US20220111528A1
公开(公告)日：2022-04-14
申请号：US17559646
申请日：2021-12-22
Applicant: Intel Corporation
Inventor： Akash Dhamasia , Florian Geissler , Ralf Graefe , Neslihan Kose Cihangir , Michael Paulitsch , Rafael Rosales , Norbert Stoeffler
Abstract: A computing device, including: a memory configured to store computer-readable instructions; and unintended human motion detection processing circuitry configured to execute the computer-readable instructions to cause the computing device to: interpret a human action; receive autonomous mobile robot (AMR) sensor data from an AMR sensor; and detect whether the human action is intended or unintended, wherein the detection is based on a predicted human action, a current human emotional or physical state, the interpreted human action, and the AMR sensor data.
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公开(公告)号：US20210403004A1
公开(公告)日：2021-12-30
申请号：US17471411
申请日：2021-09-10
Applicant: Intel Corporation
Inventor： Ignacio J. Alvarez , Marcos Carranza , Ralf Graefe , Francesc Guim bernat , Cesar Martinez-spessot , Dario Oliver , Selvakumar Panneer , Michael Paulitsch , Rafael Rosales
Abstract: Techniques are disclosed to address issues related to the use of personalized training data to supplement machine learning trained models for Driver Monitoring System (DMS), and the accompanying mechanisms to maintain confidentiality of this personalized training data. The techniques disclosed herein also address issues related to maintaining transparency with respect to collected sensor data used in a DMS. Additionally, the techniques disclosed herein facilitate the generation of a digital representation of a driver for use as supplemental training data for the DMS machine learning trained models, which allow for DMS algorithms to be tailored to individual users.
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公开(公告)号：US12082082B2
公开(公告)日：2024-09-03
申请号：US17131161
申请日：2020-12-22
Applicant: Intel Corporation
Inventor： Florian Geissler , Ralf Graefe , Michael Paulitsch , Yang Peng , Rafael Rosales
CPC classification number: H04W4/40 , G06F18/217 , G06N20/00 , G06V20/56 , G06V20/58
Abstract: Described herein is a high confidence ground truth information service executing on a network of edge computing devices. A variety of participating devices obtain high confidence ground truth information relating to objects in a local environment. This information is communicated to the ground truth information service, where it may be verified and aggregated with similar information before being communicated as part of an acquired ground truth dataset to one or more subscribing devices. The subscribing devices use the ground truth information, as included in the ground truth dataset, to both validate and improve their supervised learning systems.
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9.发明申请公开(公告)号：US20210309261A1
公开(公告)日：2021-10-07
申请号：US17352560
申请日：2021-06-21
Applicant: Intel Corporation
Inventor： Rafael Rosales , Ignacio J. Alvarez , Florian Geissler , Neslihan Kose Cihangir , Michael Paulitsch
Abstract: Techniques are disclosed to detect, inform, and automatically correct typical awareness-related human driver mistakes. This may include those that are caused by a misunderstanding of the current situation, a lack of focus or attention, and/or overconfidence in any currently-engaged assistance features. The disclosure is directed to the prediction of vehicle maneuvers using driver and external environment modeling. The consequence of executing a predicted maneuver is categorized based upon its risk or danger posed to the driving environment, and the vehicle may execute various actions based upon the categorization of a predicted riving maneuver to mitigate or eliminate that risk.
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公开(公告)号：US11054265B2
公开(公告)日：2021-07-06
申请号：US16369029
申请日：2019-03-29
Applicant: Intel Corporation
Inventor： Florian Geissler , Ralf Graefe , Michael Paulitsch , Rainer Makowitz
Abstract: Methods, systems, and apparatus, including computer programs encoded on non-transitory computer storage medium(s), are directed to improving completeness of map information and data related to maps created through sensor data. Map completeness can be improved by determining object completeness and coverage completeness of a generated map and reducing amount of unknown areas of the generated map.
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