Researchers Submit Patent Application, “Mobile Device And System For Identifying And/Or Classifying Occupants Of A Vehicle And Corresponding Method Thereof”, for Approval (USPTO 20220080976): Swiss Reinsurance Company Ltd.
2022 APR 06 (NewsRx) -- By a
The patent’s assignee is
News editors obtained the following quote from the background information supplied by the inventors: “Up-to-date engineered car driving (including completely manually controlled driving, partially autonomous car driving, driverless cars, self-driving cars, robotic cars) is associated with vehicles that are capable of sensing their environment and operational status or use. At the same time, the use of sensors in cellular mobile phones, in particular in so called “smart phones”, has strongly increased in recent years, making it possible to monitor or time-dependent track the operation mode of the smart phone as well as surroundings, use or even behavior of the user. Modern, mobile smart phones comprise a variety of sensors, as touchscreens, accelerometers, gyroscopes, GPS, cameras, microphones etc., allowing to capture a vast mixture of contextual parameters during the use of the mobile device. On the other side, digital systems of the vehicle can include transceivers and/or interfaces that are configured to communicate with a driver’s mobile phone. Typically, the driver can utilize the vehicle computer system to handle hands-free communication utilizing vehicle features. For example, the conversation can be output on vehicle speakers and a vehicle mic may be utilized to pick up. Other occupants and/or passengers can be in the vehicle when a driver has initiated a voice session.
“The communication between the mobile device and the computer system of the vehicle can related to other data than voice transmission, since modern automotive engineered vehicles are capable of detecting a wide variety of operational or surrounding parameters using for example radar, LIDAR (measuring device to measure distances by means of laser light), GPS (Global Positioning System), odometry (measuring device for measuring changings in position over time by means of using motion sensor data), and computer vision. In modern cars, advanced control systems often interpret sensory information to identify appropriate navigation paths, as well as obstacles and relevant signage. The sensors may comprise active and passive sensing devices, wherein sensors are physical converter devices measuring a physical quantity and converting the measured physical quantity into a signal that can be read by an observer or by another instrument, circuit or system. Commonly used sensors for automotive motor vehicle or mobile cell phones are for example infrared sensors containing an infrared emitter, and an infrared detector, for example used with touchless switches, passive infrared (PIR) sensors reacting and detecting only on ambient IR such as motion sensors, speed detectors e.g. radar guns such as microwave radars using the Doppler effect (the return echo from a moving object will be frequency shifted) or IR/Laser radars sending pulses of light for determining the difference in reflection time between consecutive pulses to determine speed, ultrasonic sensors emitting a sound and detecting the echo to determine range, accelerometers measuring the rate of change of the capacitance and translating it into an acceleration by means of a proof mass, gyroscopes measuring a mass oscillating back and forth along the first axis, and plates on either side of the mass in the third direction where the capacitance changes when a rotation is detected around the second direction, IMU-sensors (Inertial Measurement Unit) providing a sensor with a full 6-degrees of freedom by using a combination of accelerometer and gyroscope, force sensing resistor e.g. for contact sensing, touchscreens based on resistive, capacitive or surface acoustic wave sensing, location sensors such as GPS (Global Positioning System), triangulation or cell identification systems, visual sensors such as cameras and computer visions, SIM-based or RFID-based (Radio-Frequency Identification) sensors, or environment sensors as moisture sensors, humidity sensors, temperature sensors, magnetometer etc. Due to the improved assistance by such digital systems and sensory data, vehicle driving are steadily becoming safer by incorporating automated systems to monitor operations of the vehicle while the vehicle is in motion and to provide coordinated alerts and assistance as needed. However, difficulties remain in reliably detecting the presence of vehicle occupants and accurately identify them as driver or passenger, and/or even classify them as children, small adults, and/or according to other classifications, and particularly in differentiating between classifications. Accurate classification can be critical when the vehicle is attempting to assist or enact safety measures to protect the occupant or in measuring occupant-specific risk-exposure parameters.
“However, often it is desirable, not to rely on the automotive sensory of the vehicle, for example since the mobile phones of the passengers are not connected to the automotive digital systems of the vehicle and thus a biunique identification of all the occupants of a vehicle cannot be performed. The correct identification of driver versus passenger are not only important for applications related to the driver and his phone, as e.g. for technical assistance, real-time monitoring, accident identification or risk measurements etc. but also in relation to possible assistance by a passenger. For example, there are technical applications for enhancing the driving safety of senior passengers. Though it is known for teenage drivers, that mutual distractions may create an elevated risk for major crashes, studies show that the presence of passengers can be protective for seniors. These studies show that crash rates are lower when seniors drive with a passenger that when they drive alone. It turns out that passengers can be helpful copilots by keeping drivers alert, assisting with navigation, waring of impending hazards, and operating the radio, heat and air-conditioning controls, or using the cell phone.
“There is a considerable interest and need in leveraging the recent advances in the sensing, data storage-processing and wireless communications technologies in vehicles to introduce smart functionalities more fundamentally. One of the aims is to offer drivers and passengers, not only safer, but also a personalized and more pleasant driving experience and technical support. This goes beyond the classical Advanced Driver Assistance Systems (ADAS) and route guidance services to customizing the vehicle interior and adapting its systems to the driver “and” passenger(s) profiles and preferences, for example seat positions, setting reminders, temperature control, HMI, infotainment system, etc. Nevertheless, such functionalities rely fundamentally on identifying the vehicle occupants, particularly when a vehicle has multiple occupants. They also may require labeled pertinent data, i.e. for a known occupants, from various sources such as in-vehicle sensing systems or smartphones or even infrastructure, to learn preferences, profiles and behaviors. Biunique driver and passenger identification is also relevant to insurance telematics, for instance the driving style can allow automated setting the driver’s or a passenger’s risk-transfer premium by appropriate electronic risk-transfer systems. Apart from using the smart phone sensory data, establishing the style can be based on recorded data from the vehicle
“The remarkably fast growth of smartphone ownership has motivated the move towards exploiting smartphones versatile set of sensors, such as the Global Navigation Satellite System (GNSS) receiver and Inertial Measurement Units (IMUs), in automotive applications. Examples include: traffic state estimation, navigation, driver assistance and many others. Interestingly, the problem of determining the smartphone to vehicle position is closely related (or corresponds) to the driver and passenger(s) identification task. This capitalizes on the premise that the smartphone is: (i) usually in the vicinity of its owner, and (ii) a personal item, which is not shared with other users, unlike a (smart) key-fob, which can be used/shared by multiple vehicle drivers. Smartphone-to-vehicle localization, which covers inside and/or outside the vehicle, hence enables identifying the present vehicle user(s), i.e. if the smartphone owner is the driver or, front or rear passenger. Recognition can be performed before or after entering the car. Locating the phone within the vehicle can, amongst others, be employed to minimize distractions induced by using a smartphone whilst driving. For example, the driver’s smartphone services and functionalities can be accordingly restricted. Additionally, realizing a connected cooperative vehicle environment is currently attracting another interest from researchers and OEMs around the world, mainly due to its importance to autonomous driving. This includes vehicle to vehicle, vehicle to infrastructure and vehicle to cloud communications, typically with stringent latency and performance requirements. Thus, a smartphone user identification solution can exchange data with the vehicle in a connected set-up. It can also have access to the vehicle data (e.g. doors signal, which indicates whether a given vehicle door is opened or closed), user’s calendar, journeys history, etc.”
There is additional background information. Please visit full patent to read further.”
As a supplement to the background information on this patent application, NewsRx correspondents also obtained the inventors’ summary information for this patent application: “It is one object of the present invention to provide techniques for a system and method to detect and/or classify a vehicle occupant, such as a driver or a passenger seated within the cockpit or other seats of a vehicle without having the disadvantages of prior art systems. Independent in dedicated in-vehicle hardware possibly providing an alternative solution to the problem (e.g. retina or face scanners presented in CES2018), the invention shall provide an appropriate system and method for identification and/or classify a vehicle occupant solely based on the available sensors of a smartphone of a smartphone user, e.g. applicable to the realization of usage-based risk-transfer as PAYD (
“According to the present invention, these objects are in particular achieved with the features of the independent claims. In addition, further advantageous embodiments can be derived from the dependent claims and the related descriptions.
“According to the present invention, the above-mentioned objects for identifying and/or classifying an occupant of a vehicle based on sensory data measured by a plurality of sensors of a cellular mobile device of the occupant, are in particular achieved in that, the plurality of sensors of the cellular mobile device at least comprise an accelerometer and a gyroscope, the mobile device further comprising one or more wireless connections, wherein by at least one of the wireless connection, the cellular mobile device acts as a wireless node within a cellular data transmission network by means of antenna connections of the cellular mobile device to the cellular data transmission network, and the plurality of sensors being connected to a monitoring mobile node application of the mobile device, wherein the monitoring mobile node application captures usage-based and/or user-based telematics data of the cellular mobile device and/or the user of the cellular mobile device, in that the mobile device measures gravitational acceleration movement sensory data by means of the accelerometer based on measuring parameters obtained from the accelerometer, wherein vehicle entering or exiting movement patterns of the user are detected from the acceleration movement sensory data at least comprising pattern for base axis and degree of rotation associated with a vehicle entrance or exit of the user, and in that the detected vehicle entering or exiting movement patterns of the user trigger as input features the recognition of a vehicle entering or exiting movement of the user by performing a decision-tree classification on the input features to rule out whether the user entered or exited from a left or right side of the vehicle. The inventive system and method detects the user rotation direction while entering (and exiting) the car, using the information obtained from the gyroscope sensor (yaw) through a machine learning algorithm. The mobile telecommunication apparatus can e.g. comprise at least a GPS module (Global Positioning System) and/or geological compass module based on a 3-axis teslameter and a 3-axis accelerometer, and/or gyrosensor or gyrometer, and/or a MEMS accelerometer sensor comprising or consisting of a cantilever beam with the seismic mass as a proof mass measuring the proper or g-force acceleration, and/or a MEMS magnetometer or a magnetoresistive permalloy sensor or another three-axis magnetometer. To provide the wireless connection, the mobile telecommunications apparatus can, for example, act as wireless node within a corresponding data transmission network by means of antenna connections of the mobile telecommunication apparatus, in particular mobile telecommunication networks such as 3G, 4G, 5G LTE (Long-Term Evolution) networks or mobile WiMAX or other GSM/EDGE and UMTS/HSPA based network technologies etc., and more particular with appropriate identification means as SIM (Subscriber Identity Module) etc. The mobile telecommunication apparatus and the monitoring cellular mobile node application can (but does not have to) for example be connected to an on-board diagnostic system and/or an in-car interactive device, wherein the mobile telecommunications apparatus capture usage-based and/or user-based automotive data of the motor vehicle and/or user. The mobile telecommunications apparatus can for example provide the one or more wireless connections by means radio data systems (RDS) modules and/or positioning system including a satellite receiving module and/or a mobile cellular phone module including a digital radio service module and/or a language unit in communication the radio data system or the positioning system or the cellular telephone module. The satellite receiving module can for example comprise a Global Positioning System (GPS) circuit and/or the digital radio service module comprises at least a Global System for
The claims supplied by the inventors are:
“1. A method for identifying and/or classifying a user of a vehicle based on sensory data measured by a plurality of sensors of a mobile device of the user, the plurality of sensors at least comprising an accelerometer and a gyroscope, the mobile device comprising at least one wireless connection, wherein by the at least one wireless connection, the mobile device acts as a wireless node within a cellular data transmission network by antenna connections of the mobile device to the cellular data transmission network, the plurality of sensors being connected to a monitoring mobile node application of the mobile device, and wherein the monitoring mobile node application captures usage-based and/or user-based telematics data of the mobile device and/or the user of the mobile device, the method comprising: measuring, by processing circuitry, gravitational acceleration movement sensory data based on measuring parameters obtained from the accelerometer; detecting, by the processing circuitry, vehicle entering or exiting movement patterns of the user from the acceleration movement sensory data at least comprising a pattern for a base axis and a degree of rotation associated with a vehicle entrance or exit of the user; and triggering, by the processing circuitry using the detected vehicle entering or exiting movement patterns of the user, as input features recognition of a vehicle entering or exiting movement of the user by performing a decision-tree classification on the input features to determine whether the user entered or exited the vehicle from a left side or a right side of the vehicle.
“2. The method for identifying and/or classifying the user of the vehicle according to claim 1, wherein the gravitational acceleration movements are correlated with an orientation of the mobile device building a smartphone reference system.
“3. The method for identifying and/or classifying the user of the vehicle according to claim 2, further comprising, in order to detect an exact moment when the user is entering or exiting the vehicle, detecting acceleration in an up or down direction related to an earth reference system from the acceleration movement sensory data and measuring a variance of discontinuities in acceleration signals in the smartphone reference system.
“4. The method for identifying and/or classifying the user of the vehicle according to claim 3, wherein the acceleration movement sensory data are triggered for a timely gap associable with a time window just before opening a door of the vehicle immediately before entering the vehicle or a downwards movement performed during a sitting movement.
“5. The method for identifying and/or classifying the user of the vehicle according to claim 4, wherein upon detecting a movement pattern suitable for the sitting movement, the acceleration movement sensory data are triggered for rotations with an overlap with the sitting movement, and a decision tree is performed to classify the user as a driver or a passenger depending on a counterclockwise or clockwise direction of rotation.
“6. The method for identifying and/or classifying the user of the vehicle according to claim 5, wherein any detected movement pattern is classified as the sitting movement or an other movement.
“7. The method for identifying and/or classifying the user of the vehicle according to claim 5, wherein, for separating the movement pattern from timely gaps, a variance of the acceleration in the up or down direction is processed by a threshold filter, wherein the acceleration in the up or down direction corresponds to a signal rotated in the earth reference system.
“8. The method for identifying and/or classifying the user of the vehicle according to claim 7, wherein the acceleration in the variance of the up or down direction at a certain time is generated over a fixed time window centered around the certain time, wherein the variance of the up or down direction depends on a length of the time window.
“9. The method for identifying and/or classifying the user of the vehicle according to claim 8, wherein the length of the time window is set to one second or more to ensure proper sampling of a full oscillation.
“10. The method for identifying and/or classifying the user of the vehicle according to claim 9, wherein the acceleration movement sensory data are triggered for the movement pattern, wherein the movement pattern is recognized as the sitting movement, in response to a time-dependent duration of the movement pattern being measured close to that of a predefined or captured average sitting movement.
“11. The method for identifying and/or classifying the user of the vehicle according to claim 9, wherein the acceleration movement sensory data are triggered for the movement pattern, wherein the movement pattern is recognized as the sitting movement, in response to the movement pattern being measured to be definably close to a rotation in an x-y plane compatible with an entrance or exiting.
“12. The method for identifying and/or classifying the user of the vehicle according to claim 9, wherein the acceleration movement sensory data are triggered for the movement pattern, wherein the movement pattern is recognized as the sitting movement, in response to the movement pattern being measured to be definable near to a discontinuity in acceleration components in the smartphone reference system.
“13. The method for identifying and/or classifying the user of the vehicle according to claim 12, wherein additional rule-based classifications are added based on a specific type of discontinuity.
“14. The method for identifying and/or classifying the user of the vehicle according to claim 1, further comprising, upon detecting movement patterns best matching a sitting movement, determining gyroscope movement sensory data corresponding to the acceleration movement sensory data, wherein an integral of rotations in an x-y plane in the earth reference system are detected which are sufficiently close to the sitting movement.
“15. The method for identifying and/or classifying the user of the vehicle according to claim 14, wherein a counterclockwise rotation is associated with an entrance or exit of the user from the left side of the vehicle.
“16. The method for identifying and/or classifying the user of the vehicle according to claim 15, wherein the counterclockwise rotation is measured to be at least 40°.
“17. The method for identifying and/or classifying the user of the vehicle according to claim 14, wherein a clockwise rotation is associated with an entrance or exit of the user from the right side of the vehicle.
“18. The method for identifying and/or classifying the user of the vehicle according to claim 17, wherein the clockwise rotation is measured to be at least 40°.
“19. The method for identifying and/or classifying the user of the vehicle according to claim 1, further comprising: classifying orientations of the mobile device as driver orientations and passenger orientations, determining, a first time duration that the mobile device is oriented in the driver orientations and a second time duration that the mobile device is oriented in the passenger orientations; performing a comparison of the first time duration to the second time duration; and classifying the user of the mobile device as a driver or a passenger based on the comparison.”
For additional information on this patent application, see: CERRUTI, Benedetta; GENOVESE,
(Our reports deliver fact-based news of research and discoveries from around the world.)
Studies from Cedars Sinai Medical Center Provide New Data on Hormones (Which Us States’ Medicaid Programs Provide Coverage for Gender-affirming Hormone Therapy and Gender-affirming Genital Surgery for Transgender Patients?: a State-by-state …): Hormones
AM Best Assigns Credit Ratings to Federated Specialty Insurance Company; Affirms Credit Ratings of Federated Mutual Insurance Company and Main Subsidiaries
Advisor News
- Innovative financial literacy’s greatest hits
- Gen Z not following the typical path to retirement
- Survey finds some support for DOL fiduciary rule
- Nonprofit involvement: How do you get business and WIIFM?
- Workers still concerned about financial well-being
More Advisor NewsAnnuity News
- Corebridge Financial tallies strong annuity, life sales numbers in Q3
- Equitable hones in on annuity delivery across channels after strong Q3
- Maintaining annuity sales momentum with Gen X
- Best’s Special Report: Smaller Companies Face Cash Flow Crunch from Uptick in U.S. Life/Annuity Surrenders
- Jackson Increases Access to RILA Product through Distribution Partnership with JPMorganChase
More Annuity NewsHealth/Employee Benefits News
- Pacific Prime Unveils Cost of International Health Insurance Report 2024
- Researchers at Boston University Have Reported New Data on Information Technology (Generalizability of Heat-related Health Risk Associations Observed In a Large Healthcare Claims Database of Patients With Commercial Health Insurance): Information Technology
- Studies Conducted at University of North Carolina on Managed Care Recently Reported (Modeling the Impact of Decreasing Waiting Period Length for Medicaid Sterilization: a Multi-site Cohort Study): Managed Care
- Findings on Pediatrics Reported by Investigators at Arizona State University (Has Access To Paraprofessionals Changed? a Cross-decade, Cross-cohort Analysis): Pediatrics
- Insurance industry veteran Steve Nelson named president of CT-based Aetna, subsidiary of CVS Health
More Health/Employee Benefits NewsLife Insurance News
- AM Best Removes From Under Review With Developing Implications and Upgrades Credit Ratings of Merit Life Insurance Co.
- Automatic Shelf Registration Statement Form S 3ASR
- Greg Lindberg plea deal reached on federal fraud charges
- AM Best Affirms Credit Ratings of Standard Insurance Company and its Affiliate Companies, and Pacific Guardian Life Insurance Company, Limited
- WTW appoints Karen Grote as Division LOB Leader for North America Life Practice
More Life Insurance News