Vehicle exception event management systems
Exception event recorders and analysis systems include: vehicle mounted sensors arranged as a vehicle event recorder to capture both discrete and non-discrete data; a discretization facility; a database; and an analysis server all coupled together as a computer network. Motor vehicles with video cameras and onboard diagnostic systems capture data when the vehicle is involved in a crash or other anomaly (an ‘event’). In station where interpretation of non-discrete data is rendered, i.e. a discretization facility, captured data is used as a basis for production of supplemental discrete data to further characterize the event. Such interpreted data is joined to captured data and inserted into a database in a structure which is searchable and which supports logical or mathematical analysis by automated machines. A coupled analysis server is arranged to test stored data for prescribed conditions and upon finding such, to initiate further actions appropriate for the detected condition.
1. A discretization system configured to receive vehicle event information and form vehicle event records related to previously detected vehicle events, the discretization system comprising:
one or more physical computer processors configured to:
receive first non-discrete sensory data that has been captured by a video camera, wherein the video camera has a field-of-view that includes an environment about a vehicle; and
receive first discrete quantitative data related to operation of the vehicle; and
a user interface, wherein the user interface receives one or more of entry and/or selection of manual interpretation information pertaining to the first non-discrete sensory data from a human interpreter, wherein the manual interpretation information includes discrete numeric values;
wherein the one or more physical computer processors are further configured to:
determine second discrete quantitative data based on the discrete numeric values included in the manual interpretation information;
form a vehicle event record that includes the first non-discrete sensory data, the first discrete quantitative data, and the second discrete quantitative data; and
transfer the vehicle event record to a remote computing device that is external to the vehicle.
2. The system of claim 1 , wherein the one or more physical computer processors are configured such that one or more of the first non-discrete sensory data, the first discrete quantitative data, and the second discrete quantitative data include observations related to operator behavior, the observations related to operator behavior related to one or more of a collision, a near collision, a driving error, a distraction, a position of a head of an operator, an eye position of the operator, a hand position of the operator, talking by the operator, a lane departure, a lane position, a number of lanes in a direction of travel, a road type, a following distance, a number of visible vehicles, or a vehicle environment.
3. The system of claim 1 , further comprising a data store configured to electronically store the first non-discrete sensory data, the first discrete quantitative data, and the second discrete quantitative data, the data store comprising one or more of a relational database, a NoSQL database, or a Hadoop data store.
4. The system of claim 3 , wherein the data store is configured such that the stored data is associated with a vehicle event and a vehicle event timeline in the data store.
5. The system of claim 1 , wherein the user interface includes one or more of a keypad, a button, a switch, a keyboard, a knob, a lever, a display screen, a touch screen, a speaker, a microphone, an indicator light, an audible alarm, a printer, or a tactile feedback device.
6. The system of claim 1 , wherein the one or more physical computer processors are further configured to automatically discretize a portion of the first non-discrete sensory data via one or more of a neural network or logistic regression;
wherein the vehicle event record further includes the automatically discretized portion of the first non-discrete sensory data.
7. The system of claim 1 , wherein the first non-discrete sensory data includes one or more of audio recording data or visual information representing a vehicle environment of the vehicle, the visual information acquired by one or more cameras, the vehicle environment including spaces in and around an interior and an exterior of the vehicle, the one or more cameras including one or more of a forward looking camera, a driver view camera, a passenger view camera, a rear vehicle view camera, or a side vehicle view camera.
8. The system of claim 1 , wherein the user interface is configured to provide a graphical representation of the first discrete quantitative data, the graphical representation of the first discrete quantitative data including a graphical representation of one or more of vehicle acceleration, vehicle speed, engine speed, vehicle gear, vehicle brake position, vehicle steering wheel position, throttle position, engine load, vehicle angular velocity, gear ratio, lane departure, following distance, a collision warning, rollover protection system activation, fishtailing protection system activation, a speedometer, an engine RPM gage, or a force gauge.
9. The system of claim 1 , wherein the one or more physical computer processors are configured such that the vehicle event record includes coaching information.
10. The system of claim 1 , wherein the one or more physical computer processors are further configured to generate and facilitate distribution of a report based on multiple individual vehicle events.
11. A method for receiving vehicle event information and forming vehicle event records related to previously detected vehicle events, the method comprising:
receiving first non-discrete sensory data that has been captured by a video camera, wherein the video camera has a field-of-view that includes an environment about a vehicle;
receiving first discrete quantitative data related to operation of the vehicle; and
receiving one or more of entry and/or selection of manual interpretation information pertaining to the first non-discrete sensory data from a human interpreter via a user interface, wherein the manual interpretation information includes discrete numeric values;
determining second discrete quantitative data based on the discrete numeric values included in the manual interpretation information;
forming a vehicle event record that includes the first non-discrete data, the first discrete quantitative data, and the second discrete quantitative data;
transferring the vehicle event record to a remote computing device that is external to the vehicle.
12. The method of claim 11 , wherein one or more of the first non-discrete sensory data, the first discrete quantitative data, and the second discrete quantitative data include observations related to operator behavior, the observations related to operator behavior related to one or more of a collision, a near collision, a driving error, a distraction, a position of a head of an operator, an eye position of the operator, a hand position of the operator, talking by the operator, a lane departure, a lane position, a number of lanes in a direction of travel, a road type, a following distance, a number of visible vehicles, or a vehicle environment.
13. The method of claim 11 , further comprising electronically storing the first non-discrete sensory data, the first discrete quantitative data, and the second discrete quantitative data in a data store, the data store comprising one or more of a relational database, a NoSQL database, or a Hadoop data store.
14. The method of claim 13 , wherein the stored data is associated with a vehicle event and a vehicle event timeline in the data store.
15. The method of claim 11 , wherein the user interface includes one or more of a keypad, a button, a switch, a keyboard, a knob, a lever, a display screen, a touch screen, a speaker, a microphone, an indicator light, an audible alarm, a printer, or a tactile feedback device.
16. The method of claim 11 , further comprising automatically discretizing a portion of the first non-discrete sensory data via one or more of a neural network or logistic regression;
wherein the vehicle event record further includes the automatically discretized portion of the first non-discrete sensory data.
17. The method of claim 11 , wherein the first non-discrete sensory data includes one or more of audio recording data or visual information representing a vehicle environment of the vehicle, the visual information acquired by one or more cameras, the vehicle environment including spaces in and around an interior and an exterior of the vehicle, the one or more cameras including one or more of a forward looking camera, a driver view camera, a passenger view camera, a rear vehicle view camera, or a side vehicle view camera.
18. The method of claim 11 , wherein the user interface provides a graphical representation of the first discrete quantitative data, the graphical representation of the first discrete quantitative data including a graphical representation of one or more of vehicle acceleration, vehicle speed, engine speed, vehicle gear, vehicle brake position, vehicle steering wheel position, throttle position, engine load, vehicle angular velocity, gear ratio, lane departure, following distance, a collision warning, rollover protection system activation, fishtailing protection system activation, a speedometer, an engine RPM gage, or a force gauge.
19. The method of claim 11 , wherein the vehicle event record includes coaching information.
20. The method of claim 11 , further comprising generating and facilitating distribution of a report based on multiple individual vehicle events.