Aspects of the present disclosure generally relate to systems and methods for data processing, and more specifically for classifying telematics data to identify gig driving associated with vehicle trips. In one implementation, a method may include the operations of segmenting a trip of a vehicle to yield multiple segments, generating, via a feature extraction component, one or more input features associated with each segment of the multiple segments based on input data indicating driving characteristics during the trip, determining, via a gig detection component, whether the trip is associated with gig driving based on the one or more input features associated with teach segment, and outputting an indication of whether the trip is associated with gig driving based on the determination.
Methods, computer-readable media, software, and apparatuses include activating a telematics system to collect telematics data associated with operation of a vehicle during a first window of time, receiving, by a computing device associated with the vehicle, telematics data from the telematics system during the first window of time, identifying one or more parameters associated with operation of the vehicle based on analyzing the telematics data, determining whether the one or more parameters meets a safe driving threshold, and upon determining that the one or more parameters meets the safe driving threshold, transmitting the telematics data to a third party server or device.
H04W 4/38 - Services specially adapted for particular environments, situations or purposes for collecting sensor information
H04W 4/44 - Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]
3.
CONTEXT BASED PRIVACY RISK FOOTPRINT AND INCIDENT PROTECTION
Methods, computer-readable media, software, systems and apparatuses may receive, from a user device, notification of a user enrolling in a privacy incident protection application, receive, from the user device, user account information associated with one or more user accounts of the user, where the user account information includes a plurality of contextual settings, determine a risk footprint associated with the user based on the user account information, monitor the one or more user accounts, receive an indication of an incident based on monitoring the one or more user accounts and based on the risk footprint, and transmit an incident notification to a data server provider associated with the incident. The incident notification may include instructions to perform a mitigation action associated with the incident.
Aspects of the disclosure relate to computing platforms that utilize improved machine learning techniques to identify vehicle problems and control ancillary computing systems. A computing platform may receive vibration data corresponding to a vehicle component. Using one or more machine learning models and based on the vibration data, the computing platfomi may identify a vehicle problem corresponding to the vibration data. After identifying the vehicle problem, the computing platform may transmit one or more commands directing the autonomous vehicle control system to autonomously navigate a vehicle to a service facility, where transmitting the one or more commands directing the autonomous vehicle control system to autonomously navigate the vehicle to the service facility causes the autonomous vehicle control system to autonomously navigate the vehicle to the service facility.
Methods, systems, and apparatuses are described for engaging autonomous driving algorithms based on driver frustration levels and vehicle conditions. A frustration level of a driver of a vehicle may be determined using one or more sensors. Based on a determination that the frustration level satisfies a threshold, one or more automated driving algorithms which may be engaged by the vehicle to improve the safety of the driver may be determined. The threshold may be based on a road segment traveled by the vehicle, the user, or similar considerations. Based on a determination that the frustration level satisfies a threshold, engagement of the one or more automated driving algorithms may be caused.
B60W 30/182 - Selecting between different operative modes, e.g. comfort and performance modes
B60W 60/00 - Drive control systems specially adapted for autonomous road vehicles
B60W 50/00 - CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT - Details of control systems for road vehicle drive control not related to the control of a particular sub-unit
6.
AUTONOMOUS DRIVING ALGORITHM EVALUATION AND IMPLEMENTATION
Methods and systems for autonomous driving algorithm evaluation are described herein. A computing device may receive, via telematics sensors associated with a vehicle, telematics data corresponding to one or more trips taken by the vehicle during a period of time. Portions of the telematics data corresponding to use of an autonomous driving algorithm may be determined. One or more performance metrics of the autonomous driving algorithm may be determined based on the portions of the telematics data corresponding to use of the autonomous driving algorithm. The one or more performance metrics may be compared to one or more other performance metrics, such as those corresponding to other autonomous driving algorithms. An autonomous vehicle score may be assigned to the autonomous driving algorithm. Based on the autonomous vehicle score, an indication of a second autonomous driving algorithm may be sent to the vehicle.
B60W 30/00 - Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
7.
CONTROL PLATFORM USING MACHINE LEARNING FOR REMOTE MOBILE DEVICE WAKE UP
Aspects of the disclosure relate to using machine learning for remote wake up of a mobile device. A computing platform may receive historical data corresponding to driving trip patterns. The computing platform may train a machine learning model using the historical data corresponding to the driving trip patterns. The computing platform may receive initial data corresponding to a particular individual, and input the initial data into the machine learning model, which may cause output of a predicted trip start time of a driving trip of the particular individual. The computing platform may send, to a mobile device corresponding to the particular individual, one or more commands directing the mobile device to wake up prior to the predicted trip start time and to initiate collection of driving trip data corresponding to the driving trip, which may cause the mobile device to be configured for the collection of driving trip data.
Methods, computer-readable media, software, and apparatuses include receiving sensor data from a sensor system associated with a vehicle during operation of the vehicle over a plurality of modes of operation, computing, based on the sensor data, a vehicle fingerprint comprising one or more vehicle characteristics over the plurality of modes of operation, monitoring additional received sensor data from the sensor system during further operation of the vehicle, determining whether an anomaly exists based on comparing the additional received sensor data to the vehicle fingerprint, and based upon determining that an anomaly exists, providing an alert to a communication interface associated with the vehicle.
B60R 25/32 - Detection related to theft or to other events relevant to anti-theft systems of vehicle dynamic parameters, e.g. speed or acceleration
H04W 4/38 - Services specially adapted for particular environments, situations or purposes for collecting sensor information
H04W 4/44 - Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]
9.
VEHICLE VALUATION ENGINE TO DETERMINE VALUATION BASED ON USAGE AND FAULT HISTORY
Methods, computer-readable media, software, and apparatuses may assist in determining the value of a vehicle, based on vehicle usage information, sensor data, and/or fault codes generated by the vehicle. The sensor data and/or the fault codes may be compared to a pre- determined grouping, and the vehicle value may be based in part on a cost of a repair associated with the pre-determined grouping.
Aspects of the disclosure relate to computing platforms that utilize machine learning to reduce false positive/negative collision output generation. A computing platform may apply machine learning algorithms on received data to generate a collision output. In response to generating the collision output indicating a collision, the computing platform may identify a data collection location. If the data collection location is within a predetermined radius of a false positive collection location, the computing platform may modify the collision output to indicate a non-collision. If the data collection location is not within the predetermined radius, the computing platform may compute a score using telematics data and compare the score to a predetermined threshold. If the score does not exceed the predetermined threshold, the computing platform may modify the collision output to indicate a non- collision. If the score exceeds the predetermined threshold, the computing platform may affirm the collision output indicating a collision.
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
B60R 21/013 - Electrical circuits for triggering safety arrangements in case of vehicle accidents or impending vehicle accidents including means for detecting collisions, impending collisions or roll-over
Aspects of the disclosure relate to computing platforms that utilize third party data for customized output generation. A computing platform may receive encrypted data corresponding to a travel history. The computing platform may decrypt a portion of the encrypted data, resulting in first decrypted travel history data. The computing platform may direct a user device to display the first decrypted travel history data, along with a first option to continue decrypting a subsequent portion of the encrypted data and a second option to delete the first decrypted travel history data. After receiving a selection of the first option, the computing platform may decrypt the subsequent portion of the encrypted data. After determining that the encrypted data is fully decrypted, the computing platform may process the decrypted data to generate a customized product output, and may direct the user device to display the customized product output.
Methods, computer-readable media, software, and apparatuses may determine, for a geographic region and based on geolocation data, a plurality of sub-regions, where each sub- region of the plurality of sub-regions may include real properties with a shared profile. The system may associate, with each sub-region, a collection of coordinate pairs, where each coordinate pair comprises a latitude and a longitude, and the collection describes a boundary of a geometric shape corresponding to the sub-region. The system may associate, with the geographic region, geometric shapes corresponding to the plurality of sub- regions. The system may associate, with each geometric shape, a rating factor for the real properties located within the sub-region corresponding to the geometric shape. The system may store the geometric shapes and rating factors, and may generate, based on the rating factor and for the real properties located within the sub-region, an output, and provide the generated output.
Aspects of the disclosure relate to computing platforms that utilize improved machine learning techniques for dynamic device quality evaluation. A computing platform may receive driving data from a mobile device. Using the driving data, the computing platform may compute a plurality of driving metrics, which may include: a geopoint expectation rate score, a trips per day rank score, a consecutive geopoint time difference score, a global positioning system (GPS) accuracy rating score, and a distance between consecutive trips score. By applying a machine learning model to the plurality of driving metrics, the computing platform may compute a device evaluation score, indicating a quality of the driving data received from the mobile device. Based on the device evaluation score, the computing platform may set flags, which may be accessible by a driver score generation platform, causing the driver score generation platform to perform an action with regard to the mobile device.
A portable radio (100) provides a voice control feature which advantageously enables radio users to perform talk group changes by using voice as an input medium to the radio device. Activation of a voice control button (110) and verbal entry of a valid talk group control command enables a change in talk group. The portable radio (100) comprises a controller (102) having a code plug (120) pre-programmed with a plurality of talk group alias names, and an automatic speech recognition (ASR) engine (118) providing voice control entry detection to the portable radio. The controller (102) enables a change in talk group in response to the ASR engine (118) detecting that the voice control entry is a valid talk group control command. Shortened audible confirmations of talk group change are generated using the alias names.
Methods, computer-readable media, software, and apparatuses may determine, based upon edge-computing operations, that a vehicular trip has been initiated and cause one or more sensors to collect vehicle data. One or more trip segments for at least a portion of the vehicular trip may be determined. In some aspects, for each trip segment, a first plurality of time features and a second plurality of frequency features may be determined, and may be concatenated with a third plurality of GPS features to form a feature vector. An accuracy measure may be determined based on the feature vector, and a mode for the vehicle may be predicted.
Methods and systems disclosed herein describe a universal access layer that allows a plurality of applications to obtain data and/or information from a plurality of heterogeneous data stores. The universal access layer may include one or more application data objects to validate requests, transform a format of the request, determine which data stores comprise the requested data and/or information, encrypt the request, combine responses into a single response, and retransform the response prior to sending it to the requesting application. By using the universal access layer, applications may improve the speed with which they access data and/or information from the plurality of heterogeneous data stores.
G06F 7/00 - Methods or arrangements for processing data by operating upon the order or content of the data handled
G06F 15/16 - Combinations of two or more digital computers each having at least an arithmetic unit, a program unit and a register, e.g. for a simultaneous processing of several programs
17.
APPLYING MACHINE LEARNING TO TELEMATICS DATA TO PREDICT ACCIDENT OUTCOMES
Systems and methods in accordance with embodiments of the invention can obtain and use a variety of telematics and other data to predict potential claim or accident outcomes arising from a variety of incidents, such as automobile accidents. The claim or accident outcomes, such as parts of the vehicle damaged, accident category, expected liabilities, and many others, can be predicted based on the telematics and other data, such as accelerometer data, heading data, location/GPS, barometer, gyroscope, magnetometer data, and the like. The machine learning classifiers that can be generated are trained on historical data, consisting of claims, telematics, and/or other relevant data. In a variety of embodiments, the telematics data can be captured using a telematics device installed in the vehicle and/or via a mobile device associated with the vehicle.
Aspects of the disclosure relate to computing platforms that utilize improved natural language processing techniques for performance evaluation and training. A computing platform may automatically determine, based on audio transcription files, a model for dynamic performance evaluation and training, which may be dynamically updated as additional audio transcription files are received. The computing platform may receive and analyze an additional audio transcription file using natural language processing and the model, which may result in proficiency scores. Based on the proficiency scores, the computing platform may calculate an overall proficiency score and identify areas for improvement associated with the first individual. Based on the areas for improvement, the computing platform may determine performance feedback tailored to the individual and may send, to a user device associated with the individual, the performance feedback.
Methods, computer-readable media, software, and apparatuses may retrieve, from a computing device at a vehicle, driving data, and determine, based on the driving data, a range of time when a driver of the vehicle has a low likelihood of accessing a web resource over a network. An online activity may be detected for an account associated with the driver. In some aspects, a time of the online activity may be compared to the range of time. Based upon a determination that the time of the online activity is within the range of time, a potentially unauthorized activity may be identified. In some aspects, in response to the potentially unauthorized activity, one or more steps may be triggered to protect the driver from the potentially unauthorized activity.
G06F 21/00 - Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
G06F 21/78 - Protecting specific internal or peripheral components, in which the protection of a component leads to protection of the entire computer to assure secure storage of data
G06F 21/80 - Protecting specific internal or peripheral components, in which the protection of a component leads to protection of the entire computer to assure secure storage of data in storage media based on magnetic or optical technology, e.g. disks with sectors
20.
PROCESSING SYSTEM FOR DYNAMIC EVENT VERIFICATION & SENSOR SELECTION
Aspects of the disclosure relate to computing platforms that utilize improved techniques for dynamic event verification. A computing platform may receive first source data comprising driving data associated with a vehicle over a time period. Based on the first source data, the computing device may determine that the vehicle experienced an event, resulting in an event output. In response to determining the event output, the computing device may generate a request for second source data associated with the vehicle over the time period. The computing device may receive, from a sensor device, the second source data. Based on a comparison of the first source data to the second source data, the computing platform may determine an event comparison output. The computing platform may determine that the event comparison output exceeds a predetermined comparison threshold, and may send an indication of an event in response.
B60W 30/08 - Predicting or avoiding probable or impending collision
H04W 4/38 - Services specially adapted for particular environments, situations or purposes for collecting sensor information
H04W 4/44 - Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]
H04W 4/46 - Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for vehicle-to-vehicle communication [V2V]
H04W 4/90 - Services for handling of emergency or hazardous situations, e.g. earthquake and tsunami warning systems [ETWS]
B60W 40/10 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to vehicle motion
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G08G 1/01 - Detecting movement of traffic to be counted or controlled
Systems and methods in accordance with embodiments of the invention can obtain and use a variety of telematics data to classify trips taken by a vehicle. Trip models can be generated based on telematics data captured during the operation of a vehicle. A variety of features of the trip model, such as the timing and/or location of stops made by the vehicle during one or more trips, can be used to classify the trip as a business trip or a personal trip. In several embodiments, machine classifiers are trained to classify features within the trip models based on historical trips that have been classified as business trips or personal trips. A number of trip models can be combined with other driver attributes to classify a particular vehicle and/or driver as engaged with a transportation network company.
G07C 5/00 - Registering or indicating the working of vehicles
G07C 5/02 - Registering or indicating driving, working, idle, or waiting time only
G07C 5/06 - Registering or indicating driving, working, idle, or waiting time only in graphical form
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G07C 5/12 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time in graphical form
Methods and systems disclosed herein describe a canonical model that sets forth a standardized schema that represents data entities and their relationships as a logical data structure across multiple business units. A schema validator module may validate application-specific schema against the canonical module. Additionally, legacy and/or existing applications may be upgraded, through a transformation module, to comply with the canonical model. The transformation module may transform application-specific data and/or information to the standardized schema, and vice versa, to ensure that legacy and/or existing applications may communicate with applications and/or processing engines that comply with the standardized schema.
Systems including one or more sensors, coupled to a vehicle, may detect sensor information and provide the sensor information to another computing device for processing. A system includes one or more sensors, coupled to a vehicle and configured to detect sensor information, and a computing device configured to communicate with one or more mobile sensors to receive the mobile sensor information, communicate with the one or more sensors to receive the sensor information, and analyze the sensor information and the mobile sensor information to identify one or more risk factors.
Systems and methods are disclosure for using sensors to deliver educational content to vehicle users during critical events. One method comprises: receiving, by a first computing device having at least one processor and from a user device of a vehicle user via a wireless data connection, a notification of a critical event for a vehicle of the vehicle user and a vehicle identification of the vehicle; receiving, from the user device via the first wireless data connection, user input soliciting educational content to remedy the critical event; determining, based on the received user input, a first set of search parameters; for each of the search parameters in the first set of search parameters, selecting educational content for a first list of educational content from a second list of educational content; and displaying, on the user device, the first list of educational content based on the first set of search parameters.
Methods, computer-readable media, software, and apparatuses may calculate and inform a consumer of company privacy scores corresponding to companies with which the consumer has a corresponding account, or for a company associated with a website that a consumer may visit. A consumer privacy score may also be determined, based on the company privacy scores. The company privacy scores may be based on a calculation including elements of a privacy practice of the corresponding company and elements of a privacy policy of the corresponding company.
26.
MULTI-COMPUTER PROCESSING SYSTEM FOR DYNAMICALLY EXECUTING RESPONSE ACTIONS BASED ON MOVEMENT DATA
Methods, computer-readable media, systems, and/or apparatuses for evaluating movement data to identify a user as a driver or non-driver passenger are provided. In some examples, movement data may be received from a mobile device of a user. The movement data may include sensor data including location data, such as global positioning system (GPS) data, accelerometer and/or gyroscope data, and the like. Additional data may be retrieved from one or more other sources. For instance, additional data such as usage of applications on the mobile device, public transportation schedules and routes, image data, vehicle operation data, and the like, may be received and analyzed with the movement data to determine whether the user of the mobile device was a driver or non-driver passenger of the vehicle. Based on the determination, the data may be deleted in some examples or may be further processed to generate one or more outputs.
Methods, computer-readable media, software, and apparatuses are provided to assist a user and vendor in completing an online trusted transaction. Trusted vendor websites are verified and user identities are confirmed through a cyber-security safe logon credentialing system. The vendor can be confident that the user identity has been verified to be who they say they are and the user can be confident that they are using a trusted verified vendor website.
Systems and methods are disclosed for providing roadside service through a synchronized interactive voice response (IVR) system and graphical user interface (GUI). One method may include: receiving, based on an incoming phone call from a vehicle user device, a request for roadside service for a disabled vehicle of a vehicle user; sending a text to a phone number of the vehicle user device, wherein the text includes a link to a mobile application for roadside service requests; receiving, from the vehicle user device and via the mobile application, information associated with the request for roadside service; determining, based on a location sensor of the vehicle user device, a location of the disabled vehicle; matching a roadside service provider with the disabled vehicle based on the request for roadside service; and enabling the vehicle user to track the service status of the roadside service provider through the mobile application.
G06Q 50/40 - Business processes related to the transportation industry (shipping G06Q 10/83)
H04W 4/021 - Services related to particular areas, e.g. point of interest [POI] services, venue services or geofences
H04W 4/44 - Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]
H04W 12/30 - Security of mobile devices; Security of mobile applications
G10L 15/22 - Procedures used during a speech recognition process, e.g. man-machine dialog
Systems, apparatuses, and methods for providing roadside assistance services are described herein. The system can include network computing devices and computing devices associated with vehicles and service vehicles. Requests for roadside services can be automatically assigned to an available service provider. Service providers can be ranked based on a variety of criteria and requests can be assigned based on the ranking. The ranking of service providers can be adjusted based on the performance of the service provider. If a service provider takes too long to respond to a request, the request can be automatically declined and an alternative service provider can be selected.
Methods, computer-readable media, software, and apparatuses may assist the user in understanding their unique digital footprint and the connections from the data within the footprint to the user's connections online and in the physical world. The determined information may be visually displayed to the user along with recommendations regarding digital safety.
H04L 51/52 - User-to-user messaging in packet-switching networks, transmitted according to store-and-forward or real-time protocols, e.g. e-mail for supporting social networking services
Methods, computer-readable media, software, and apparatuses may assist a consumer in deleting personal information held by a data broker. Entities holding the consumer's personal information may be discovered and automated actions for purging or deleting the consumer's personal information may be determined. The methods, computer-readable media, software, and apparatuses may assist the consumer in updating privacy settings associated with accounts at various entities.
A system including a processor and memory may provide for automated support communications, such as communications with individuals who need assistance. Automated communications may use one or more factors to determine how to adjust communications according to the needs of a user. For example, automated communications may be adjusted based on, e.g., a keyword used by a user in the user's communications, or a location associated with the user's mobile device or user vehicle. Automated communications may be adjusted in timing, frequency, or content. One or more external events (e.g., phone call, dispatch request, additional automated communication) may be triggered based on the automated communications.
H04W 64/00 - Locating users or terminals for network management purposes, e.g. mobility management
H04W 4/02 - Services making use of location information
H04W 4/40 - Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P]
H04W 4/90 - Services for handling of emergency or hazardous situations, e.g. earthquake and tsunami warning systems [ETWS]
G07C 5/00 - Registering or indicating the working of vehicles
G08B 1/00 - Systems for signalling characterised solely by the form of transmission of the signal
G08B 25/01 - Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems characterised by the transmission medium
G10L 15/18 - Speech classification or search using natural language modelling
Systems, methods, and computer-readable media, are disclosed in which a variety of data describing the condition of an object can be obtained and probabilistic likelihoods of causes and/or value of damages to the object can be calculated. In a variety of embodiments, data obtained from third-party systems can be utilized in these calculations. Any of a number of machine classifiers can be utilized to generate the probabilistic likelihoods and confidence metrics in the calculated liabilities. A variety of user interfaces for efficiently obtaining and visualizing the object, the surrounding geographic conditions, and/or the probabilistic likelihoods can further be utilized as appropriate to the requirements of specific applications of embodiments of the invention.
Methods, computer-readable media, software, and apparatuses may assist a consumer in keeping to their preferred privacy preferences when making a purchase online. Differences between the privacy policy of a vender and the privacy preferences of the consumer may be output for display to the consumer, along with alternative vendor recommendations, including vendors having privacy policies more closely match with the privacy preferences of the consumer.
Systems, apparatuses, and methods for providing roadside assistance services are described herein. The system may include network computing devices and computing devices associated with user vehicles and service vehicles. The system may predict incoming requests for roadside assistance services, and may allocate service providers among various geographical regions and/or time slots to handle the incoming requests. The system may receive a request for a roadside assistance service from a user. The system may select an appropriate service provider to assist the user, and may assign the service request to the selected service provider.
Aspects of the disclosure relate to a dynamic processing system for roadside service control and output generation. A computing platform may receive, from a client device, video content corresponding to a disabled vehicle, which may include geotagging information corresponding to a location of the disabled vehicle. Based on the video content and the geotagging information, the computing platform may determine a provider output indicating a potential service provider for assisting with the disabled vehicle. The computing platform may send, to the client device, an indication of the provider output. In response to receiving an indication that the potential service provider is acceptable, the computing platform may send a request to dispatch a driver of the potential service provider to the location of the disabled vehicle.
38 ABSTRACT Aspects of the disclosure relate to a dynamic processing system for roadside service control and output generation. A computing platform may receive, from a client device, video content corresponding to a disabled vehicle, which may include geotagging information corresponding to a location of the disabled vehicle. Based on the video content and the geotagging information, the computing platform may determine a provider output indicating a potential service provider for assisting with the disabled vehicle. The computing platform may send, to the client device, an indication of the provider output. In response to receiving an indication that the potential service provider is acceptable, the computing platform may send a request to dispatch a driver of the potential service provider to the location of the disabled vehicle. Date Recue/Date Received 2023-08-08
Systems, apparatuses, and methods for providing roadside assistance services are described herein. The system may include network computing devices and computing devices associated with user vehicles and service vehicles. The system may predict incoming requests for roadside services, and may allocate service providers among various geographical regions and/or time slots to handle the incoming requests. The system may receive a request for a roadside service from a user. The system may select an appropriate service provider to assist the user, and may assign the service request to the selected service provider.
Systems and methods in accordance with embodiments of the invention can proactively determine if an individual is likely in need of roadside assistance. Information can be collected from the individual's phone, including the person's location, the type of road, ambient noise, and/or motion of nearby objects. If it is determined that the individual likely needs roadside assistance, the system can proactively contact the individual to see if roadside assistance is desired, and if so, initiates roadside assistance. The system also can provide helpful information, such as safety information, and/or automatically contact other individuals to alert them of the roadside event and the location of the individual.
H04W 4/44 - Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]
G07C 5/00 - Registering or indicating the working of vehicles
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G08G 1/127 - Traffic control systems for road vehicles indicating the position of vehicles, e.g. scheduled vehicles to a central station
According to some aspects of this disclosure a roadside assistance application programming interface (API) may allow any type of application, internet of things device, voice recognition device, and others to provide roadside assistance functionality. According to some aspects of this disclosure a device may communicate with sensors or an on-board diagnostics system of a vehicle and retrieve vehicle data. The device may recommend a service based on the vehicle data. The device may send a request for roadside assistance. The device may be used to enroll a user as a member of a roadside assistance benefits program. The above mentioned steps may all be performed via a single application running on the device. According to some aspects of this disclosure a device may process a roadside assistance request and determine a roadside assistance service provider to send to a user that requested roadside assistance.
H04W 64/00 - Locating users or terminals for network management purposes, e.g. mobility management
H04W 4/02 - Services making use of location information
G08B 25/01 - Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems characterised by the transmission medium
41.
DATA PROCESSING SYSTEM WITH MACHINE LEARNING ENGINE TO PROVIDE OUTPUT GENERATION FUNCTIONS
Methods, computer-readable media, systems, and/or apparatuses for providing offer and insight generation functions are provided. For instance, user input may be received requesting generation of an offer. In response to receiving the request, an application may be transmitted to a device, such as a mobile device of a user. In some examples, the application may be executed by the device and may facilitate establishing a communication session with a third party system, identifying and extracting data from the third party system, and transmitting the extracted data to an entity for evaluation. In some examples, evaluation by the entity may include generating one or more insights, outputs and the like. In some arrangements, the evaluation may be performed using machine learning and, in some examples, may be performed in real-time or near real-time.
G06F 21/32 - User authentication using biometric data, e.g. fingerprints, iris scans or voiceprints
G06F 21/36 - User authentication by graphic or iconic representation
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
Aspects of the disclosure provide a computer-implemented method and system for the assignment of crowdsourced roadside assistance service providers to distressed vehicles/drivers requiring roadside assistance. The methods and systems may include a roadside assistance service provider system with a collection module, an assignment module, and a feedback module. The collection module collects roadside assistance service provider information and historical statistics from real-world information and stores the information in a database that may then be analyzed using particular rules and formulas. The assignment module assigns particular roadside assistance service providers to particular distressed vehicles/drivers based on one or more characteristics. The feedback module may provide near real-time cues to the roadside assistance service provider's mobile device, such as alerting when the amount of time spent on a task exceeds a predefined threshold, flagging high priority tasks/assignments, providing a technical reference for the repair.
Aspects of the disclosure relate to enhanced dynamic training response output generation control systems with enhanced dynamic training response output determinations. A computing platform may receive, from the user device and in response to an initial dynamic training interface, a training request input. The computing platform may send, to an NLU engine, the training request input and commands directing the NLU engine to perform natural language understanding and processing on the training request input to determine a natural language result output. Using the natural language result output, the computing platform may determine third party data sources that correspond to the natural language result output, and may request source data from the third party data sources. Using the source data and the natural language result output, the computing platform may generate a dynamic training response output, and may direct the user device to cause display of the dynamic training response output.
Electronic display systems, including roadside display devices, vehicle-based devices, personal mobile devices, advertising servers and/or networks, and/or additional external data sources may operate individually or in combination to identify vehicle locations, driving routes, driver and passenger characteristics, driving behavior and patterns, telematics data, and the like. Vehicle and individual characteristics and/or telematics data may be determined based on data received from traffic cameras, vehicle-based devices, personal mobile devices, telematics devices, software applications, etc. Based on the vehicle characteristics, individual characteristics, and telematics data, content, such as digital display or audio content, may be determined for output on various devices, such as electronic roadside displays to be viewable by the approaching vehicles, or other devices to be accessible by associated individuals. Various techniques may be used to determine customized content. Additionally, certain systems may be interactive to allow user responses and follow-up content via on-board vehicle or user devices.
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
H04W 4/021 - Services related to particular areas, e.g. point of interest [POI] services, venue services or geofences
H04W 4/44 - Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]
45.
DATA PROCESSING SYSTEM WITH MACHINE LEARNING ENGINE TO PROVIDE ROADSIDE ASSISTANCE FUNCTIONS
Arrangements for receiving requests for roadside assistance, generating user interfaces and using machine learning to generate roadside assistance instructions are provided. A request for roadside assistance may be received. A user and one or more partners may be identified based on the request. A profile associated with the user, partner or the like may be identified. A user interface may be generated based on the profile and may include features unique to the profile, partner, or the like. In some arrangements, the interface may include a first portion and a second portion. Selection of an option from the first portion may cause the system to identify data for display in the second portion and cause the data to be displayed in the second portion. Machine learning may be used to determine or identify one or more roadside assistance instructions and a roadside assistance instruction may be generated and executed.
Aspects of the disclosure relate to enhanced telematics processing systems with improved third party source data integration features and enhanced customized driving output determinations. A computing platform may receive telematics data and third party source data. The computing platform may enrich the telematics data using the third party source data. After generating the enriched telematics data, the computing platform may use machine learning algorithms and datasets to validate the enriched telematics data. The computing platform may ingest, via a batch ingestion process, the enriched telematics data. For example, the computing platform may store the enriched telematics data and generate additional enriched telematics data until expiration of a predetermined period of time. The computing platform may ingest the enriched telematics data associated with each trip. Once the enriched telematics data has been ingested, the computing platform may generate a standardized common trip format output for each trip.
Aspects of the disclosure relate to enhanced selectable item availability processing systems with improved content and configuration update capability and enhanced selectable item availability output determinations. A computing platform may receive a selectable item availability configuration output comprising a configuration update to the selectable item availability output and a selectable item availability content output comprising a content update to the selectable item availability output. Based on the selectable item availability configuration output and the selectable item availability content output, the computing platform may generate an updated selectable item availability output. The computing platform may receive a request to access the selectable item availability output. The computing platform may generate one or more commands to cause display of the updated selectable item availability output and may send, to a user device, the updated selectable item availability output along with the one or more commands.
G06F 3/0481 - Interaction techniques based on graphical user interfaces [GUI] based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance
Systems and methods in accordance with arrangements described herein can include identifying a variety of accounts associated with a user and determining a set of actions that can be taken with respect to the accounts. For instance, upon death of a user, a predetermined set of actions can be executed to transfer one or more assets as defined in a digital will. The accounts can be identified by scanning one or more accounts associated with the user. The accounts associated with the user and/or the account actions for the accounts can be automatically maintained over time. On an account transfer event, each of the accounts can be automatically transferred and/or closed in accordance with the determined account actions. In many embodiments, a password manager is maintained to facilitate the review of accounts and the performance of the appropriate actions on the occurrence of a transfer event.
A system for cryptographically transmitting and storing identity tokens and/or activity data among spatially distributed computing devices. The system comprises an identity chain and an activity chain. Identity data associated with a user may be used to generate an identity token. The identity token may be transmitted to a plurality of computing devices for verification. Based on a verification of the identity token, the identity token may be stored in the identity chain. A request to perform an activity may be received, and identity data associated with the user may be received in order to authenticate the user. Based on the received identity data, generate an identity token for the user. The identity token may be compared to the identity token stored in the identity chain, and the user may be authenticated based on the comparison. An activity token for the activity may be generated and stored.
H04L 9/32 - Arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system
Methods, computer-readable media, software, and apparatuses may assist in proactively warning a consumer they are a victim or possible target of a cyber-attack or cyber-threat. To discover whether a consumer may be a victim, the methods, computer-readable media, software, and apparatuses will monitor the Surface Web, Deep Web, and Dark Web for potential cyber-threats and cyber-attacks. If one is discovered, the methods, computer-readable media, software, and apparatuses will compare the criteria of victims of targeted in the cyber-attack and compare that criteria with consumer profiles. If a consumer profile matches the criteria, the methods, computer-readable media, software, and apparatuses will notify the consumer of the threat.
Systems and apparatuses for capturing an image of a vehicle for which roadside assistance is being requested are provided. The image may be captured by a mobile device and the mobile device may geotag location information to the image. The image and associated geotag location information may then be processed to determine a location of the vehicle and a roadside assistance issue for which service is being requested. The image may be further analyzed to determine a context including, a make, model and/or year of the vehicle, whether special equipment is needed to service the vehicle, whether the vehicle is located in a particular situation (e.g., within a structure, in a ditch, or the like). The information obtained from the image may be used to determine a type of service to provide to the vehicle and to identify one or more service providers to dispatch to the vehicle.
Systems, methods, computer-readable media, and apparatuses for identifying and executing one or more interactive condition evaluation tests to generate an output are provided. In some examples, user information may be received by a system and one or more interactive condition evaluation tests may be identified. An instruction may be transmitted to a computing device of a user and executed on the computing device to enable functionality of one or more sensors that may be used in the identified tests. A user interface may be generated including instructions for executing the identified tests. Upon initiating a test, data may be collected from one or more sensors in the computing device. The data collected may be transmitted to the system and may be processed using one or more machine learning datasets to generate an output.
Systems and methods are disclosed for managing the processing and execution of models that may have been developed on a variety of platforms. A multi-model execution module specifying a sequence of models to be executed may be determined. A multi-platform model processing and execution management engine may execute the multi-model execution module internally, or outsource the execution to a distributed model execution orchestration engine. A model data monitoring and analysis engine may monitor the internal and/or distributed execution of the multi-model execution module, and may further transmit notifications to various computing systems.
Event-based connected vehicle control and response systems, methods, and apparatus are disclosed. An example method comprises identifying the occurrence of an event, storing first data corresponding to apparatus operation for a first threshold amount of time prior to the event, during the occurrence of the event, and for a second threshold amount of time after the event, determining whether a responsive object is involved in or near the event, in response to determining that the responsive object is involved in or near the event, transmitting the first data to the responsive object, and receiving, from the responsive object, second data, analyzing the first data and the second data to determine a party at-fault for the event, aggregating the first data and second data into an event report, and causing, automatically, a response to be initiated through an entity associated with the party at-fault.
B60R 21/013 - Electrical circuits for triggering safety arrangements in case of vehicle accidents or impending vehicle accidents including means for detecting collisions, impending collisions or roll-over
G05D 1/24 - Arrangements for determining position or orientation
G05D 1/693 - for avoiding collisions between vehicles
55.
PROCESSING SYSTEM HAVING MACHINE LEARNING ENGINE FOR PROVIDING CUSTOMIZED USER FUNCTIONS
Systems and apparatuses for generating customized user output are provided. The system may collect sensor data, associated with the user, from a variety of sources. The system may use the sensor data to generate a customized user output. The system may analyze the sensor data, and determine, based on the sensor data and the customized user output, one or more user recommendation outputs. The system may update the customized user output based on additional or subsequent sensor data, and/or based on whether or not the user recommendation output was completed, as determined from subsequent sensor data.
Aspects of the disclosure relate to processing remotely captured sensor data. A computing platform having at least one processor, a communication interface, and memory may receive, via the communication interface, from a user computing device, sensor data captured by the user computing device using one or more sensors built into the user computing device. Subsequently, the computing platform may analyze the sensor data received from the user computing device by executing one or more data processing modules. Then, the computing platform may generate trip record data based on analyzing the sensor data received from the user computing device and may store the trip record data in a trip record database. In addition, the computing platform may generate user record data based on analyzing the sensor data received from the user computing device and may store the user record data in a user record database.
G01D 21/00 - Measuring or testing not otherwise provided for
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G05D 1/228 - Command input arrangements located on-board unmanned vehicles
G05D 1/24 - Arrangements for determining position or orientation
Aspects of the disclosure relate to using vehicle telematics data to assess parameters associated with vehicle operation. In some instances, a driving assessment system may include a first computing device associated with a user in a vehicle and a second computing located remotely from the first computing device. The first computing device may collect, by way of one or more of an accelerometer and global positioning system (GPS), vehicle operational data and vehicle locational information associated with the vehicle and corresponding to a trip of the vehicle and may transmit such information to the second computing device. The second computing device may identify actionable and second order actionable trip data from the vehicle operational data and vehicle locational information and may calculate a behavior score for the trip.
One or more devices in a data analysis computing system may be configured to receive and analyze movement data and determine driving trips based on the received data. The driving trips may be used along with the movement data to authenticate drivers based on a determined driver profile.
Aspects of the disclosure relate to using systemic logic based on one or more escalation control thresholds to manage fulfillment of a dispatch. In some instances, a dispatch management server may receive data for each of one or more escalation control thresholds, monitor fulfillment of a dispatch after an incident based on each of the one or more escalation control thresholds, identify that at least one of the one or more escalation control thresholds has been surpassed, identify an available dispatch specialist out of a plurality of dispatch specialists to receive task management responsibilities, and assign the task management responsibilities to the dispatch specialist.
Systems and methods are disclosed for guidance, control, and testing of autonomous vehicle features and a driver's response thereto. The system may activate a plurality of autonomous driving features of an autonomous vehicle. In response to a determination to initiate a driving test, the system may generate an indication to a driver of the autonomous vehicle of the initiation of the driving test and may deactivate or adjust parameters of one or more of the plurality of autonomous driving features. The system may receive, from one or more sensors of the autonomous vehicle or one or more sensors of a mobile computing device within the autonomous vehicle, driving data associated with the autonomous vehicle. Based on the driving data associated with the autonomous vehicle, the system may determine the driver's response time and actions taken by the driver during the driving test. Moreover, in response to a determination to end the driving test, the system may reactivate the one or more of the plurality of autonomous driving features previously deactivated or may readjust previously adjusted parameters. In some aspects, based on the driver's response time and actions taken by the driver during the driving test, a drive score may be generated for the driver.
B60W 50/00 - CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT - Details of control systems for road vehicle drive control not related to the control of a particular sub-unit
B60W 10/184 - Conjoint control of vehicle sub-units of different type or different function including control of braking systems with wheel brakes
Aspects of the disclosure relate to controlling an autonomous vehicle to respond to a detected collision. An autonomous vehicle control system may receive sensor data associated with an autonomous vehicle in which the autonomous vehicle control system is installed. The autonomous vehicle control system may analyze the sensor data in real-time as the sensor data is received and may detect an occurrence of a collision involving the autonomous vehicle. In response to detecting the occurrence of the collision, the autonomous vehicle control system may generate claim information based on the sensor data and may process the claim information based on at least one insurance profile maintained by the autonomous vehicle control system. Then, the autonomous vehicle control system may generate a claim notification based on processing the claim information and may send the claim notification to a vehicle management computer system.
A multi-stop route selection system may include a telematics device associated with a vehicle having one or more sensors arranged therein, a mobile device, and a server computer. The server computer may receive driving data of a driver of the vehicle and a vehicle location from the telematics device, determine one or more driving behaviors of the driver based on the driving data, receive data regarding a calendar of the driver from the mobile device, identify a plurality of appointments in the calendar, determine a route comprising multiple destinations for the driver based on the vehicle location, the one or more driving behaviors, and the plurality of appointments, transmit the route to the mobile device, receive a request to add a new destination to the route from the mobile device, generate a modified route comprising the new destination, and transmit the modified route for the driver to the mobile device.
H04L 67/12 - Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
A fuel analysis system is described configured to assist vehicle drivers/users in preventing damage to their vehicles caused by bad fuel. Bad fuel can leave a driver and passengers stranded on the road in need of emergency road side service, and in many instances, results in permanent damage to the vehicle. The disclosed fuel analysis system describes an enhanced bad fuel sensor system that measures a delta in vehicle operation data to identify and in many instances, pre-emptively alert, a user of a vehicle of bad fuel. The fuel analysis system may use crowdsourcing through aggregation of refueling event profile records from a plurality of vehicles' telematics devices to increase the accuracy with which bad fuel is detected.
Methods, computer-readable media, software, and apparatuses may assist a consumer in keeping track of a consumer's accounts in order to prevent unauthorized access or use of the consumer's identified accounts. To discover the various accounts, the methods, computer-readable media, software, and apparatuses can monitor at least a consumer's email accounts, web browser history, and web cache. The discovered accounts may be displayed to the consumer along with recommendations and assistance for closing unused or unwanted accounts to prevent unauthorized access or use.
Methods, computer-readable media, software, and apparatuses may assist a consumer in keeping track of a consumer's accounts in order to prevent unauthorized access or use of the consumer's identified accounts. To discover the various accounts, the methods, computer- readable media, software, and apparatuses can monitor at least a consumer's email accounts, web browser history, and web cache. The discovered accounts may be displayed to the consumer along with recommendations and assistance for closing unused or unwanted accounts to prevent unauthorized access or use.
G06F 21/57 - Certifying or maintaining trusted computer platforms, e.g. secure boots or power-downs, version controls, system software checks, secure updates or assessing vulnerabilities
G06F 21/50 - Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems
Aspects of the disclosure relate to controlling autonomous vehicles to provide automated emergency response functions. A computing platform may receive vehicle data associated with a vehicle from an on-board vehicle monitoring system associated with the vehicle. Subsequently, the computing platform may detect an occurrence of an emergency at a location. Thereafter, the computing platform may select an autonomous vehicle to respond to the emergency at the location based on autonomous vehicle state information. Then, the computing platform may generate one or more dispatch commands directing the autonomous vehicle to move to the location and execute one or more emergency response functions. Subsequently, the computing platform may send, to an on-board autonomous vehicle control system associated with the autonomous vehicle, the one or more dispatch commands directing the autonomous vehicle to move to the location and execute the one or more emergency response functions.
G08G 1/00 - Traffic control systems for road vehicles
G05D 1/00 - Control of position, course, altitude, or attitude of land, water, air, or space vehicles, e.g. automatic pilot
G07C 5/00 - Registering or indicating the working of vehicles
G07C 5/02 - Registering or indicating driving, working, idle, or waiting time only
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
67.
ELECTRONIC DISPLAY SYSTEMS CONNECTED TO VEHICLES AND VEHICLE-BASED SYSTEMS
Electronic digital display systems, including roadside display devices, vehicle-based devices, personal mobile devices, intermediary servers, advertising servers, and/or additional external data sources may operate individually or in combination to identify one or more vehicle locations, driving routes, driver and passenger characteristics, and the like. Vehicle and individual characteristics may be determined based on data received from traffic cameras, vehicle-based devices, personal mobile devices, and/or other data sources. Based on the vehicle characteristics, individual characteristics, driving data and driving patterns, and the like, digital content may be determined for electronic roadside displays to be viewable by the approaching vehicles, and/or other digital display devices to be viewable by associated individuals via other display devices and at other times. Various techniques may be used to determine customized digital content. Additionally, certain systems may be interactive to allow user responses and follow-up content via on-board vehicle devices or other user devices.
A personal information assistant computing system may include a user computing device having a processor and a non-transitory memory device storing instructions. The personal information assistant may receive a user accessible input as a natural language communication from the user, which may be analyzed by a personal information assistant to determine a task to be performed by the virtual information assistant. The personal information assistant may be personalized to the user using encrypted user information. The personal information assistant communicates with a remote computing system in performance of a computer- assisted task, wherein the first personal information assistant interacts as a proxy for the user in response to at least one response received from the remote computing system. The personal information assistant may communicate the results of the task to the user via a user information screen and/or an audio device.
ELECTRICAL DATA PROCESSING SYSTEM FOR DETERMINING A NAVIGATION ROUTE BASED ON THE LOCATION OF A VEHICLE AND GENERATING A RECOMMENDATION FOR A VEHICLE MANEUVER
Systems and methods are disclosed for determining a navigation route based on the location of a vehicle and generating a recommendation for a vehicle maneuver. The method may comprise determining, based on sensor data received from a location sensor of a mobile device or a vehicle, a location of the vehicle. A computing device may determine a navigation route for navigating the vehicle from the location to a destination, and the navigation route may comprise a plurality of intersections. The computing device may determine a plurality of potential maneuvers at a first intersection of the plurality of intersections. The computing device may also determine, based on one or more factors, a navigation score for each of the plurality of potential maneuvers at the first intersection. Based on the navigation score for each of the plurality of potential maneuvers, the computing device may select a maneuver from the plurality of potential maneuvers to recommend for the vehicle.
Systems, methods, computer-readable media, and apparatuses for evaluating device usage and generating one or more outputs based on the device usage are provided. For instance, data from one or more sensors within a user personal mobile device may be received and processed to determine movement associated with the device. In addition, an amount of usage (e.g., hours, minutes, etc.) associated with the device may be received. In some examples information regarding the device or user of the device may be received. In some examples, application usage and/or types of applications used may also be received. This data may be processed and a likelihood of damage to the device may be determined. Based on this likelihood, one or more outputs may be determined.
H04M 15/00 - Arrangements for metering, time-control or time-indication
71.
ELECTRICAL DATA PROCESSING SYSTEM FOR DETERMINING A NAVIGATION ROUTE BASED ON THE LOCATION OF A VEHICLE AND GENERATING A RECOMMENDATION FOR A VEHICLE MANEUVER
Systems and methods are disclosed for determining a navigation route based on the location of a vehicle and generating a recommendation for a vehicle maneuver. The method may comprise determining, based on sensor data received from a location sensor of a mobile device or a vehicle, a location of the vehicle. A computing device may determine a navigation route for navigating the vehicle from the location to a destination, and the navigation route may comprise a plurality of intersections. The computing device may determine a plurality of potential maneuvers at a first intersection of the plurality of intersections. The computing device may also determine, based on one or more factors, a navigation score for each of the plurality of potential maneuvers at the first intersection. Based on the navigation score for each of the plurality of potential maneuvers, the computing device may select a maneuver from the plurality of potential maneuvers to recommend for the vehicle.
Aspects of the present disclosure describe systems, methods, and devices for vehicle mode detection based on acceleration data and location data during a trip detected by mobile devices in a vehicle. According to some examples, location data will be compared to known routeway data to detect a vehicle mode. In other examples acceleration data will be used to calculate the consistency of vehicular velocity during a trip to detect a vehicle mode. In some additional aspects, multiple analyses will be performed on the same data sets to check for false positives with vehicle mode detection.
A system including a processor and memory may provide for automatically activating or deactivating a feature of a fleet vehicle. For example, one or more fleet vehicles may include one or more of a global-positioning system, a speed governor, electronically-controlled brakes, an electronically-controlled accelerator, a speed limiter, or an on-board computer with a processor and memory. One or more features may be activated by a local or remote computing device or system. For example, a system may determine one or more recommended routes between two or more locations. The system may track a fleet vehicle's progress along a route, and activate a feature of the fleet vehicle based on the fleet vehicle following or not following the recommended route. For example, the system may cause activation of a speed limiter on the fleet vehicle, disable the fleet vehicle, and/or activate or deactivate autonomous features of the fleet vehicle.
Methods, systems, and computer-readable media, and apparatuses for optimizing policy underwriting and insurance policy coverage are described herein. Insurance information related to a new homeowner insurance policy may be retrieved from one or more insurance system databases. The insurance information may comprise an insurance policy premium. An unrestrained rating plan premium may be determined based on a plurality of premium components. The plurality of premium components may comprise at least one multiplicative factor and at least one additive factor determined from the insurance information. An underwriting score may be determined based on the unrestrained rating plan premium and the insurance policy premium. In response to determining that the underwriting score fails to meet a predetermined underwriting score threshold, the new homeowner insurance policy may be rejected.
An insurance system for home sharing may comprise a mobile device of a homeowner, one or more databases storing insurance factor data, a plurality of sensors configured to monitor one or more home features, and a server comprising one or more processors and memory. The server may be configured to receive, from the mobile device, data indicating that the homeowner is renting out a home, determine a value for frequency of rentals for the home based on the data indicating that the homeowner is renting out the home, and receive, from the plurality of sensors, monitored data for the one or more home features. The server may compute an insurance premium for the homeowner based on the value for frequency of rentals for the home, the monitored data for the one or more home features, and the insurance factor data and transmit the insurance premium to the mobile device.
A method, medium, and apparatus for educating and reducing risk to inexperienced drivers using vehicles vvith autonomous navigation systems. Data regarding a driver's past experience with vehicles and operating environments may be used to proactively warn the driver about a potential danger detected or predicted by the vehicle. An autonomous vehicle may prevent the driver from operating the vehicle under unfamiliar circumstances or from causing a collision. Data regarding a driver's past experience with vehicles and the safety features thereof may be used to mitigate risk of injury or property damage by selectively activating safety features in a new vehicle which the driver has not previously driven. Data regarding a driver's past experience with vehicles and safety features thereof may be used to determine a decreased or increased rental rate for a particular vehicle.
Systems and apparatuses for receiving data from a plurality of sensors and using the data, as well as other data, to generate a parking recommendation for a first vehicle are provided. Data may be received from sensors associated with a first vehicle for which a parking recommendation may be generated. Data may also be received from sensors associated with other vehicles and/or from one or more structures or other non-vehicle devices. In some examples, historical parking data may be extracted from a database. The collected and extracted data may be used to generate a parking recommendation for the first vehicle. In some examples, pre-stored user preferences, may be used in generating the parking recommendation as well. The parking recommendation may then be transmitted to a computing device within the first vehicle and may be displayed on the computing device.
H04W 4/44 - Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]
H04W 4/46 - Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for vehicle-to-vehicle communication [V2V]
G08G 1/137 - Traffic control systems for road vehicles indicating the position of vehicles, e.g. scheduled vehicles within the vehicle the indicator being in the form of a map
Apparatuses, systems, and methods are provided for the utilization of vehicle control systems to cause a vehicle to take preventative action responsive to the detection of a near short term adverse driving scenario. A vehicle control system may receive information corresponding to vehicle operator data and ancillary data. Based on the received vehicle operator data and the received ancillary data, a multi-dimension risk score module may calculate risk scores associated with the received vehicle operator data and the received ancillary data. Subsequently, the vehicle control systems may cause the vehicle to perform at least one of a close call detection action and a close call detection alert to lessen the risk associated with the received vehicle operator data and the received ancillary data.
B60W 60/00 - Drive control systems specially adapted for autonomous road vehicles
B60Q 1/50 - Arrangement of optical signalling or lighting devices, the mounting or supporting thereof or circuits therefor the devices being primarily intended to indicate the vehicle, or parts thereof, or to give signals, to other traffic for indicating other intentions or conditions, e.g. request for waiting or overtaking
B60Q 9/00 - Arrangement or adaptation of signal devices not provided for in one of main groups
Disclosed herein is a traveling-based insurance rating system comprising a telematics device associated with a vehicle having one or more sensors arranged therein, a mobile device associated with a passenger of the vehicle, and a server computer comprising hardware, including a processor and memory. The server computer may receive driving data of a driver of the vehicle from the one or more sensors via the telematics device. The server computer may then identify one or more values of the driving data to be within one or more predetermined ranges and classify the driving data as a trip of the passenger. Based on the driving data from the trip, the server computer may determine one or more driving behaviors of the driver, calculate an insurance rating for the passenger of the vehicle based on the one or more driving behaviors of the driver, and transmit the insurance rating to the mobile device.
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
Methods, computer-readable media, software, and apparatuses may monitor consumer information in order to determine a probability of a data breach associated with a customer based on an online presence of the customer. The probability of a data breach may be used to present metrics to a consumer and/or a service provider. Further, the consumer may be presented with information indicating what factors contribute to the probability of a data breach, as well as information regarding how to reduce those factors.
The disclosure provides an early notification system to alert a driver of an approaching unsafe autonomous or semi-autonomous driving zone so that a driver may switch vehicle to a non-autonomous driving mode and navigate safely through the identified location. In response, to a determination of an upcoming unsafe autonomous or semi-autonomous driving zone, the driver or system may take appropriate actions in response to the early notification.
Systems and methods are disclosed for determining that an adverse driving event is likely to occur and utilizing accident calculus algorithms to determine and cause vehicle driving actions necessary to mitigate consequences of the adverse driving event. After determining that an adverse driving event is likely to occur, a computing device my forecast consequences of the driving event. The computing device may determine potential evasive maneuvers that may be taken responsive to the adverse driving event. Additionally, the computing device may determine consequences associated with the potential evasive maneuvers and assign a weight relative to the consequence. The computing device may compare the potential driving maneuvers based on the weighted consequences to determine a driving maneuver to take.
B60W 30/09 - Taking automatic action to avoid collision, e.g. braking and steering
B60W 30/095 - Predicting travel path or likelihood of collision
H04W 4/44 - Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]
H04W 4/80 - Services using short range communication, e.g. near-field communication [NFC], radio-frequency identification [RFID] or low energy communication
A route risk mitigation system and method using real-time information to improve the safety of vehicles operating in semi-autonomous or autonomous modes. The method mitigates the risks associated with driving by assigning real-time risk values to road segments and then using those real-time risk values to select less risky travel routes, including less risky travel routes for vehicles engaged in autonomous driving over the travel routes. The route risk mitigation system may receive location information, real-time operation information, (and/or other information) and provide updated associated risk values. In an embodiment, separate risk values may be determined for vehicles engaged in autonomous driving over the road segment and vehicles engaged in manual driving over the road segment.
Systems and methods for determining the authenticity of vehicle operational data provided by telematics or other devices are provided. Vehicle performance and/or operational data may be collected and the authenticity of the data stream may be determined based on the whether the data stream includes a watermark in a predetermined location of the data stream or whether the data stream includes a data key comprising a predetermined false vehicle performance data reading. A second data recording device may also record vehicle performance and/or operational data. Both the first and second data recording devices may provide the respective vehicle performance data to a computing device. The computing device may compare the vehicle performance data from the first and second data recording devices to determine authenticity of the vehicle measurement data.
G07C 5/00 - Registering or indicating the working of vehicles
G06F 21/64 - Protecting data integrity, e.g. using checksums, certificates or signatures
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
Systems and methods for determining the authenticity of vehicle operational data provided by telematics or other devices are provided. Vehicle performance and/or operational data may be collected and the authenticity of the data stream may be determined based on whether the data stream includes a watermark in a predetermined location of the data stream or whether the data stream includes a data key comprising a predetermined false vehicle performance data reading. A second data recording device may also record vehicle performance data and/or operational data. Both the first and second data recording devices may provide the respective vehicle performance data to a computing device. The computing device may compare the vehicle performance data from the first and second data recording devices to determine authenticity of the vehicle measurement data.
H04W 4/38 - Services specially adapted for particular environments, situations or purposes for collecting sensor information
H04W 4/44 - Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]
H04L 9/00 - Arrangements for secret or secure communications; Network security protocols
86.
DESIGNING PREFERRED VEHICLE ROUTES BASED ON DRIVING SCORES FROM OTHER VEHICLES
Systems and methods are provided for designing a preferred route for a vehicle. The route designing system receives a request from the vehicle for a preferred route from a first geographical point to a second geographical point. The route designing system analyzes the request and obtains driving scores associated with drivers of other vehicles. The route designing unit may identify a set of preferred and non-preferred vehicles based on the driving scores. The route designing system then determines a preferred route based, at least in part, on the driving scores associated with drivers of the other vehicles. The preferred route is designed to minimize the likelihood of proximity to non-preferred vehicles and maximize the likelihood of proximity to preferred vehicles.
Systems and methods are disclosed for generating a display of a navigation map. The system may comprise a historical data source device having, for example, a historical data source computer and a database storing historical data associated with one or more of vehicle accident data, traffic data, vehicle volume data, vehicle density data, road characteristic data, or weather data. The system may comprise a map data processing device having a map data processing computer and memory storing computer-executable instructions that, when executed by the map data processing computer, cause the map data processing device to, for example, determine, based on a location determining device, a location of a vehicle. The map data processing system may determine one or more historical factors based on the location of the vehicle. The map data processing system may receive, from the historical data source device and for the location, historical data associated with the one or more historical factors. Based on the location of the vehicle, one or more real time factors and real time data associated with the one or more real time factors may be calculated. The map data processing system may calculate, using the one or more historical factors and the one or more real time factors, a navigation score for each segment of a route from the location to a destination location. The map data processing system may determine one or more colors for each navigation score and/or generate a display of a navigation map comprising the one or more colors.
Systems and methods are disclosed for generating a display of one or more multi-dimensional navigation scores. The data source device may comprise a data source computer and a database storing historical data or real time data associated with a plurality of segments of road. A map data processing device may have a map data processing computer and memory storing computer-executable instructions. The map data processing device may determine a geographical location based on a location determining device, determine a segment of road associated with the geographical location, and/or receive, from the data source device, one or more of the historical data or real time data for the segment of road. The map data processing device may determine a threshold navigation score for the segment of road, determine, using the one or more of the historical data or real time data, a multi-dimensional navigation score for the segment of road, and/or determine whether the multi-dimensional navigation score for the segment of road exceeds the threshold navigation score. Based on the determination of whether the multi-dimensional navigation score for the segment of road exceeds the threshold navigation score, the map data processing device may generate a display of the multi-dimensional navigation score.
Systems including one or more sensors, coupled to a vehicle, may detect sensor information and provide the sensor information to another computing device for processing. The processing may include analyzing the sensor information to identify one or more risk objects, such as animals, pedestrians, potholes, etc. The processing may further include generating a three-dimensional (3D) risk map, which may be displayed to a passenger in the vehicle. The 3D risk map may illustrate the one or more risk objects as one or more point clouds, respectively, within a virtual world representation of the vehicle's surroundings. Such a display may be used to alert drivers to possible risks while driving. In case of an accident, the 3D risk map may also be leveraged by insurance providers to process insurance claims and to notify customers that an insurance claim has been established.
B60W 40/02 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to ambient conditions
A mobile computerized apparatus or method configured to coordinate towing facilities and roadside assistance providers and their available capacity to tow and provide roadside assistance and match users with those towing facilities and roadside assistance providers is disclosed. The apparatus or method may be configured to consider the following factors in matching the towing facilities/roadside assistance providers and users: (a) availability of nearby towing facilities; (b) telematics information from the vehicle to assist with the diagnosis/repairs; (c) preset preferences of the user; (d) insurance information (such as the type of the vehicle the user has and the user's home address); and (e) the capabilities of the towing facility.
Methods of preparing retail establishments are disclosed. An area for a retail location may be chosen and an individual may be selected to manage the retail location. The selection of the area may include an evaluation of geographical factors. From the area, a retail location may be selected based on an aggregate score of a set of characteristics of the retail location. The individual may remotely select the layout and furnishing of the retail location and may remotely monitor the progress of the preparation of the retail location. In an embodiment, the individual may be prepared to manage the retail location at a centralized location that is distinct from the area where the retail location is located.
A method of determining and optimizing the location of a new insurance agency is disclosed to increase market penetration of underrepresented markets. The method comprises the use of a scoring algorithm to rank various geographic regions or related zip codes. The scoring algorithm may be implemented by a location modeling system based on variables selected by a user.
A method and apparatus for collecting and evaluating powered vehicle operation utilizing on-board diagnostic components and location determining components or systems. The invention creates one or more databases whereby identifiable behavior or evaluative characteristics can be analyzed or categorized. The evaluation can include predicting likely future events. The database can be correlated or evaluated with other databases for a wide variety of uses.
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
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