Cambridge Mobile Telematics Inc.

Truemotion, Inc.

Zipcar, Inc.

Rafi Finegold

Brad Cordova

Dan Shiebler

Kevin Farrell

Eddie Vaisman

Joe Adelmann

Philippe Bosshart

Matt McClure

Sam Cecala

Hari Balakrishnan

Sanujit Sahoo

Samuel Ross Madden

Yuting Qi

Jonathan Eric Wolfe

Brian Sachetta

Robert Scott Kobetis

Lesley Mottla

Arash Hadapanah

Gábor Tyukász

John Collins

Embodiments of the present invention relate to transportation systems. More particularly, embodiments relate to methods and systems of vehicle data collection by a user having a mobile device. In a particular embodiment, vehicle movement data (also termed herein 'driving data' or “data”) is collected, analyzed and transformed, and combinations of collected data and transformed data are used in different ways, including, but not limited to, reporting and display of the combinations.

Mobile phone application and graphical user interface for detecting and visualizing driving events using mobile phone sensors

A system for reporting accident data includes: a mobile device having a plurality of sensors; a memory; and a processor coupled to the memory. The processor is configured to perform operations including: operating the plurality of sensors to collect driving data; receiving the driving data collected over a plurality of time intervals from at least one of the plurality of sensors in the mobile device of a user during a trip in a vehicle, assigning the driving data to the trip; receiving input indicating the trip is associated with an accident, wherein the input includes additional data associated with the accident; transmitting the driving data assigned to the trip associated with the accident; and transmitting the additional data associated with the accident.

Method and system for accident detection using contextual data

Embodiments of the present invention utilize mobile devices to provide information on a user's behaviors during transportation. For example, a mobile device carried by a user can be used to detect and analyze driving behaviors during trips in vehicles. The mobile device can further be used to assign and display scores relating to the driving behaviors, scores for individual trips, and an overall driving score for the particular user.

Systems and methods for scoring driving trips

A method includes collecting motion data from a sensor of a mobile device disposed in a vehicle and processing, using at least one of a processor of the mobile device or a server remote from the mobile device, the motion data to identify a user of the mobile device as a driver of the vehicle. The method also includes detecting, using the motion data and at least one of the processor or the server, a hard braking event, generating an alert based on the detection of the hard braking event, and notifying the user, through the mobile device, of the hard braking event using the alert.

Systems and methods for sensor-based detection and alerting of hard braking events

A method for providing proactive driving alerts includes determining a road segment of interest, receiving GPS data and contextual data, and identifying a triggering condition in a vicinity of the segment of interest. The method also includes determining an applicability of the triggering condition to the segment of interest, retrieving an alert threshold corresponding to the triggering condition, and obtaining an action factor correlating to a user's driving behavior. The method further includes determining whether the action factor exceeds the alert threshold and providing a proactive alert related to the triggering condition to the user.

Method and system for driver alerts based on sensor data and contextual information

Methods and systems for presenting collected driving data

A method for determining usage of a mobile device in a vehicle by a user includes receiving a first value indicating an 'off' state of a screen of the mobile device at a first time, obtaining first movement measurements, and computing a gravity diff angle (GDA) value for the first movements. The method also includes determining that the GDA value exceeds a predefined GDA threshold value, computing summary statistics for the first movements, and classifying the summary statistics as corresponding to mobile device usage starting. The method further includes classifying the first movements of the mobile device as usage movements in response to determining that the GDA value exceeds the predefined GDA threshold, classifying the summary statistics as corresponding to mobile device usage starting, or both, and generating an indication of mobile device usage in response to classifying the first movements of the mobile device as usage movements.

Device-based systems and methods for detecting screen state and device movement

Embodiments of the present invention utilize mobile devices to provide information on a user's behaviors during transportation. For example, a mobile device carried by a user can be used to detect and analyze driving behavior. The mobile device can further be used to provide alerts based on driving behavior and to encourage and track modification of driving behavior.

Systems and methods for sensor-based detection, alerting and modification of driving behaviors

A system includes: a mobile device comprising a plurality of sensors; a display device; a memory that stores instructions; and a processor. The processor is configured to execute the instructions to: operate the plurality of sensors over a plurality of time intervals during a trip in a vehicle to collect driving data; detect, using the driving data, a driving event that occurred during the trip and cause the mobile device to collect additional data associated with the trip in response; receive the additional data associated with the trip; determine that a vehicle accident event occurred during the trip based on the driving data and the additional data; and cause the display device to output an indication of the vehicle accident event.

A method for determining usage of a mobile device in a vehicle by a user includes receiving a first value indicating an 'off' state of a screen at a first time, operating at least one sensor of the mobile device to obtain first movement measurements, and classifying the first movements as usage movements. The method also includes generating an indication of mobile device usage, receiving a second value indicating an 'on' state of the screen at a second time, operating the at least one sensor to obtain second movement measurements, and classifying the second movements as usage movements or non-usage movements. The method further includes maintaining the indication of mobile device usage in response to the second movements being classified as usage movements or changing the indication of mobile device usage to an indication of mobile device non-usage in response to the second movements being classified as non-usage movements.

Embodiments of the present invention relate to transportation systems. More particularly, embodiments relate to methods and systems of vehicle data collection by a user having a mobile device. In a particular embodiment, vehicle movement data (also termed herein 'driving data' or 'data') is collected, analyzed and transformed, and combinations of collected data and transformed data are used in different ways, including, but not limited to, reporting and display of the combinations.

A system, method, apparatus and computer program product for improved vehicle late return prediction and detection. A computer system determines an end return time by which a vehicle is to be returned by a user or member to a return location. The system receives current vehicle location data at a first predetermined time before the end return time, and the distance between the current vehicle location and return location is combined with a vehicle velocity to calculate an expected return time of the vehicle. The expected return time is compared to the end return time to determine if there will be a potential late return.

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Sharon, MA, United States of America

Rafi Finegold