Method for smartphone-based accident detection

• US 10,848,913 B2
• Filed: 03/08/2019
• Issued: 11/24/2020
• Est. Priority Date: 08/20/2015
• Status: Active Grant

• Current Assignee: Zendrive, Inc.
• Original Assignee: Zendrive, Inc.
• Inventors: Pal, Jayanta, Islam, Bipul, Choudhury, Romit Roy, Risbood, Pankaj, Matus, Jonathan, Verma, Vishal
• Primary Examiner(s): Swarthout, Brent
• Application Number:
  US16/297,178
• Publication Number:
  US 20190202448A1
• Time in Patent Office: 627 Days
• Field of Search: 340436
• CPC Class Codes: B60R 2325/205 Mobile phones
• CPC Class Codes: B60R 25/24 using electronic identifiers containing a code not memorised by the user
• CPC Class Codes: B60W 40/10 related to vehicle motion
• CPC Class Codes: G06N 7/01 Probabilistic graphical models, e.g. probabilistic networks
• CPC Class Codes: G06Q 40/08 Insurance
• CPC Class Codes: G06V 20/10 Terrestrial scenes scenes under surveillance with static cameras G06V20/52; scenes perceived from the exterior of a vehicle G06V20/56; scenes perceived from the interior of a vehicle G06V20/59
• CPC Class Codes: G06V 20/56 exterior to a vehicle by using sensors mounted on the vehicle
• CPC Class Codes: G06V 20/597 Recognising the driver's state or behaviour, e.g. attention or drowsiness
• CPC Class Codes: G06V 40/15 Biometric patterns based on physiological signals, e.g. heartbeat, blood flow
• CPC Class Codes: G07C 5/008 communicating information to a remotely located station transmission systems for measured values G08C
• CPC Class Codes: G07C 5/02 Registering or indicating driving, working, idle, or waiting time only apparatus forming part of taximeters G07B13/00
• CPC Class Codes: G07C 5/0808 Diagnosing performance data testing of vehicles G01M17/00; testing of electrical installation on vehicles G01R31/005
• CPC Class Codes: G07C 5/0866 the electronic data carrier being a digital video recorder in combination with video camera
• CPC Class Codes: G08B 25/00 Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems
• CPC Class Codes: G08B 25/001 Alarm cancelling procedures or alarm forwarding decisions, e.g. based on absence of alarm confirmation
• CPC Class Codes: G08B 25/006 Alarm destination chosen according to type of event, e.g. in case of fire phone the fire service, in case of medical emergency phone the ambulance
• CPC Class Codes: G08B 25/016 Personal emergency signalling and security systems emergency non-personal manually actuated alarm activators G08B25/12
• CPC Class Codes: G08G 1/012 from other sources than vehicle or roadside beacons, e.g. mobile networks
• CPC Class Codes: G08G 1/0129 for creating historical data or processing based on historical data
• CPC Class Codes: H04M 1/72421 with automatic activation of emergency service functions, e.g. upon sensing an alarm
• CPC Class Codes: H04M 1/72454 : according to context-related or environment-related conditions
• CPC Class Codes: H04M 2250/12 : including a sensor for measuring a physical value, e.g. temperature or motion telephones including GPS signal receivers H04M2250/10
• CPC Class Codes: H04W 4/027 : using movement velocity, acceleration information
• CPC Class Codes: H04W 4/029 : Location-based management or tracking services
• CPC Class Codes: H04W 4/40 : for vehicles, e.g. vehicle-to-pedestrians [V2P]
• CPC Class Codes: H04W 88/00 : Devices specially adapted for wireless communication networks, e.g. terminals, base stations or access point devices

Abstract

A method and system for detecting an accident of a vehicle, the method including: receiving a movement dataset collected at least at one of a location sensor and a motion sensor arranged within the vehicle, during a time period of movement of the vehicle, extracting a set of movement features associated with at least one of a position, a velocity, and an acceleration characterizing the movement of the vehicle during the time period, detecting a vehicular accident event from processing the set of movement features with an accident detection model, and in response to detecting the vehicular accident event, automatically initiating an accident response action.

Claims

1. A method for detecting a vehicular accident event with a mobile computing device located within a vehicle, the method comprising:

extracting a vehicle motion characteristic from at least one of a first location dataset and a first motion dataset collected at the mobile computing device during a first time period, wherein the vehicle motion characteristic describes the movement of the vehicle within a time window of the first time period;

comparing the vehicle motion characteristic to a motion characteristic threshold condition;

extracting an ambient pressure value from a pressure dataset collected at the mobile computing device during the first time period;

comparing the ambient pressure value to a pressure threshold condition;

in response to the vehicle motion characteristic satisfying the motion characteristic threshold condition and the ambient pressure value satisfying the pressure threshold condition;

retrieving an accident detection model,

receiving a second motion dataset collected at the mobile computing device during a second time period, the second time period later than the first time period;

detecting the vehicular accident event with the accident detection model and the second motion dataset; and

transmitting an accident-related notification in response to detecting the vehicular accident event.

2. The method of claim 1, wherein the vehicle motion characteristic comprises a vehicle speed characteristic, and further comprising, in response to the vehicle speed characteristic falling below a vehicle speed threshold, continuously collecting the pressure dataset at the mobile computing device.

3. The method of claim 1, further comprising determining an accident severity score associated with the vehicular accident event based on a maximum ambient pressure value during the first time period.

4. The method of claim 1, wherein detecting the vehicular accident event comprises determining accident-related information comprising airbag deployment data based on the ambient pressure value.

5. The method of claim 1, wherein detecting satisfaction of the motion characteristic condition comprises detecting satisfaction of the motion characteristic condition based on the vehicle motion characteristic and a traffic dataset.

6. The method of claim 5, wherein the traffic dataset describes the traffic conditions proximal the vehicle location at a time period prior to detecting satisfaction of the motion characteristic threshold condition.

7. The method of claim 1, further comprising determining a vehicular accident type describing the vehicular accident event, based on the pressure dataset, wherein the accident response action is based on the vehicular accident type.

8. The method of claim 7, wherein determining the vehicular accident type comprises determining a major collision based on airbag deployment indicated by the ambient pressure value extracted from the pressure dataset.

9. The method of claim 1, wherein transmitting the accident-related notification comprises facilitating transmission of communications for automatically deploying emergency services to a location proximal the vehicle location, based on the second motion dataset in combination with the pressure dataset.

10. The method of claim 1, wherein detecting the vehicular accident event comprises determining an accident confidence metric for the vehicular accident event based on the pressure dataset, and wherein the accident response action is based on the accident confidence metric.

11. The method of claim 1, further comprising determining a vehicular accident type describing the vehicular accident event, based on at least one of a second location dataset and the second motion dataset, wherein the vehicular accident type comprises at least one of:

a single-vehicle collision, a multi-vehicle collision, and a pedestrian collision.

12. The method of claim 11, further comprising, in response to determining the vehicular accident type, automatically generating, at the mobile computing device, an insurance claim with the vehicular accident type.