Qualcomm Incorporated

Gm Cruise Holdings LLC

Nokia Corporation

Govindarajan Krishnamurthi

Rajarshi Gupta

Saumitra Mohan Das

Vinay Sridhara

Michael Franco Taveira

Mihai Christodorescu

Mastooreh Salajegheh

Ram Gopal Lakshmi Narayanan

Seyed Ali Ahmadzadeh

Srinivas Raghavan

Stewart Alan Skomra

Deepa Suri

Tat Keung Chan

Dirk Trossen

Hemant M Chaskar

Arun Raman

Senthil Sengodan

Dana Pavel

Donald John Jones

Hermant Chaskar

Patrick J Hughes

Sreenivas Addagatla

Allan Schougaard

Ram Gopal Narayanan

Systems and methods provide for enabling an autonomous vehicle to provide road assistance to a vehicle. The autonomous vehicle can analyze sensor data about the vehicle captured by one or more of its sensors as it navigates a route. Based on the analysis of the sensor data, the autonomous vehicle can determine that the vehicle needs maintenance. The autonomous vehicle can proactively send a request, based on the determination, to initiate a towing mechanism to tow the vehicle. Based on receiving an acceptance of the request from the vehicle, the autonomous vehicle can activate the towing mechanism.

Providing roadside assistance to vehicles

The subject disclosure relates to ways to resolve autonomous vehicle (AV) routes based on verbal descriptions of landmark features. In some aspects, a process of the disclosed technology includes steps for receiving speech instructions, wherein the speech instructions indicate an autonomous vehicle (AV) destination, analyzing the speech instructions to identify one or more landmarks associated with the AV destination, and determining location information corresponding with the one or more landmarks. In some aspects, the process further includes calculating a route based on the location information corresponding with the one or more landmarks. Systems and machine-readable media are also provided.

Landmark based routing

The present technology is effective to receive a list of topics for discussion, initiate a conversation with a passenger of an autonomous vehicle, receive sensor data from sensors of the autonomous vehicle; determine, based upon sensor data received from the autonomous vehicle and the first topic, contextual information to present in the conversation with the passenger; and present the contextual information in the conversation to the passenger. The list of topics may be determined by a user. The conversation may include at least a first topic. The first topic may be included in the list of topics for discussion.

Conversational AI based on real-time contextual information for autonomous vehicles

Various methods for monitoring a target user by a robotic vehicle include tracking the target user by the robotic vehicle, detecting an object in the presence of the target user based on one or more detection criteria, determining whether the object is a potential threat to the target user based on one or more threat criteria, determining whether to notify the third party of the potential threat to the target user based on one or more notification criteria in response to determining that the object is a potential threat, and notifying the third party of the potential threat to the target user in response to determining that the third party should be notified.

Personal security robotic vehicle

An autonomous vehicle including a communication system in communication with a computing system. The computing system runs computer-executable instructions that may examine a profile of a passenger. The computer-executable instructions may include detecting a safe opportunity for the passenger to exit the autonomous vehicle. In response to detecting the safe opportunity, and if the profile of the passenger requests so, the autonomous vehicle may cause a speaker on the autonomous vehicle to audibly notify and guide the passenger to exit the autonomous vehicle safely during the safe opportunity.

Safe passenger disembarking for autonomous vehicles via audible signals

A method including sending a communication to a user device associated with the user and receiving, at the autonomous vehicle, an audible authentication code. The communication can include a location of the autonomous vehicle. The location can be effective to assist the user device to audibly provide guidance from a location of the mobile device to the location of the autonomous vehicle. The audible authentication code can be effective to assist an authentication process between the autonomous vehicle and the user.

Pick-up authentication via audible signals

In some embodiments, a method for generating a mobile device's user interface is provided. The method may include: receiving, via the mobile device, input from a user of the mobile device, the input being related to a property for presenting dynamic context-dependent informational cues; determining a context; identifying a subset of a set of informational cues, the subset being associated with the context; and predominately presenting, via the mobile device, the identified subset to the user, the presentation being predominate as compared to any presentation of other informational cues in the set of informational cues, wherein the presentation accords with the received user input.

Dynamic and configurable user interface

An autonomous vehicle including a communication system in communication with a computing system. The computing system runs computer-executable instructions that may examine a profile of a passenger. The computer-executable instructions may include authenticating between the passenger and the autonomous vehicle through the communication system, such that the authenticating results in a successful authentication of a first audible authentication signal and a second audible authentication signal.

Various methods for monitoring a target user by a drone include tracking the target user by the drone, detecting an object in the presence of the target user based on one or more detection criteria, determining whether the object is a potential threat to the target user based on one or more threat criteria, determining whether to notify the third party of the potential threat to the target user based on one or more notification criteria in response to determining that the object is a potential threat, notifying the third party of the potential threat to the target user in response to determining that the third party should be notified, receiving a response from the third party including a command, and performing an action based on the command.

Systems, methods, and devices of the various aspects enable detecting a malfunction caused by radio frequency (RF) interference. A computing device processor may identify a location of the computing device based on a plurality of real-time data inputs received by the computing device. The processor may characterize an RF environment of the computing device based on the identified location and the plurality of real-time data inputs. The processor may determine at least one RF emissions threshold based on the characterization of the RF environment. The processor may compare the characterization of the RF environment to the at least one RF emissions threshold, and may perform an action in response to determining that the characterization of the RF environment exceeds the at least one RF emissions threshold.

On-device behavioral analysis to detect malfunction due to RF interference

Various embodiments may include a computing device analyzing an image to identify one or more elements of interest in the image, identifying concepts associated with elements of interest in the image, and identifying potential elements of interest and potential concepts that are not included in the image using other information. Various embodiments may include presenting the one or more elements of interest, the one or more potential elements of interest, and the one or more concepts, receiving a user input that selects one or more of the one or more elements of interest, the one or more potential elements of interest, and the one or more concepts identified in the identified elements of interest and concepts or any combination thereof for a target image, and generating the semantic representation of the target image based on the selected elements of interest and concepts.

System and method of generating a semantic representation of a target image for an image processing operation

Various embodiments include methods, and computing devices implementing the methods, for analyzing sensor information to identify an abnormal vehicle behavior. A computing device may monitor sensors (e.g., a closely-integrated vehicle sensor, a loosely-integrated vehicle sensor, a non-vehicle sensor, etc.) in the vehicle to collect the sensor information, analyze the collected sensor information to generate an analysis result, and use the generated analysis result to determine whether a behavior of the vehicle is abnormal. The computing device may also generate a communication message in response to determining that the behavior of the vehicle is abnormal, and send the generated communication message to an external entity.

Methods and systems for utilizing information collected from multiple sensors to protect a vehicle from malware and attacks

Various embodiments include methods, and computing devices implementing the methods, for authenticating vehicle information by polling selected sensors. A server computing device receiving vehicle information from a reporting vehicle may compare the received vehicle information to contextual information to generate a comparison result, and determine whether the received vehicle information should be evaluated with greater scrutiny based on the comparison result. The server computing device may select sensors for polling based on the received vehicle information (and in response to determining that the received vehicle information should be evaluated with greater scrutiny), and poll the selected sensors to received sensor information. The server computing device may use the received sensor information to corroborate the received vehicle information, and perform a responsive action based on the result of the corroboration.

Growing community of inventors

Palo Alto, CA, United States of America

Govindarajan Krishnamurthi