Abstract: A method of determining vehicle acceleration information includes obtaining a plurality of movement measurements from a mobile device in a vehicle, and determining a plurality of gravity vectors, each of the plurality of gravity vectors associated with at least two of the plurality of movement measurements. The method further includes removing a movement measurement from the plurality of movement measurements using the plurality of gravity vectors to provide a set of remaining movement measurements. An acceleration measurement for the vehicle is determined using the remaining movement measurements.

Abstract: A mobile-device-based system for classifying a mode of transportation during a trip includes a mobile device including a location detection system and an accelerometer. The mobile device is configured to collect location data and acceleration data during the trip. The system also includes a data processing block configured to receive the location data from the mobile device, receive contextual data related to a plurality of transportation systems, and process the location data and at least a portion of the contextual data using a first transportation mode classifier associated with a first of the plurality of transportation systems and at least a second portion of the contextual data using a second transportation mode classifier associated with a second of the plurality of transportation systems. The data processing block is also configured to classify the mode of transportation during the trip and update the classifiers based on user input.

Abstract: Methods and systems are provided that enable accurate driving behavior data (e.g., vehicle acceleration data) to be obtained by a mobile device, despite the reference frames of the mobile device and the vehicle occasionally moving relative to each other. Accordingly, a user does not have to maintain a mobile device stationary relative to a vehicle in order to have a high likelihood that accurate driving data is collected.

Abstract: Embodiments of the present invention provide systems and methods for combining sensor data to measure vehicle movement. Embodiments may collect vehicle and driving data using sensors of a mobile device of a user, such as a location determination sensor and a movement determination sensor. In some embodiments, the data from the sensors may be combined to more accurately estimate vehicle movement, such as vehicle acceleration.

Abstract: A system for collecting vehicle data includes a mobile device comprising a plurality of sensors, a memory, and a processor coupled to the memory. The processor is configured to perform operations including obtaining a plurality of movement measurements from at least one of the plurality of sensors in the mobile device, determining a plurality of transportation modes using the plurality of movement measurements, and determining a mode transition using the plurality of transportation modes. The operations also include determining a transition probability using the mode transition. The operations further include creating a transition model using the transition probabilities, determining that the transition model indicates that a probability that the second transportation mode comprises driving is above a threshold, obtaining a plurality of driving movement measurements from at least one of the plurality of sensors, and determining the vehicle data using the driving movement measurements.

Abstract: Embodiments of the present invention relate to transportation systems. More particularly, embodiments relate to methods and systems for detecting airbag deployment. The method includes obtaining one or more measurements from one or more sensors of a mobile device in a vehicle during a drive, determining a change in pressure based on processing the one or more measurements, and detecting a deployment of one or more vehicle airbags based on the change in pressure.

Abstract: A system for collecting vehicle data includes a mobile device comprising a plurality of sensors, a memory, and a processor coupled to the memory. The processor is configured to perform operations including obtaining a plurality of movement measurements from at least one of the plurality of sensors in the mobile device, determining a plurality of transportation modes using the plurality of movement measurements, and determining a mode transition using the plurality of transportation modes. The operations also include determining a transition probability using the mode transition. The operations further include creating a transition model using the transition probabilities, determining that the transition model indicates that a probability that the second transportation mode comprises driving is above a threshold, obtaining a plurality of driving movement measurements from at least one of the plurality of sensors, and determining the vehicle data using the driving movement measurements.

Abstract: 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.

Abstract: A method of orienting a mobile device to a vehicle includes determining an orientation of a gravity vector and aligning a first axis of the mobile device with respect to the gravity vector. The method also includes determining an orientation of a magnetic direction and aligning a second axis of the mobile device with respect to the magnetic direction. The method further includes determining a direction of travel for the vehicle and orienting the mobile device to the vehicle.

Abstract: Some embodiments of the present invention utilize mobile devices to make an individualized prediction regarding whether a user is a driver of a vehicle on a given driving event. For example, a mobile device carried by a user can be used to detect and analyze behavior indicative of driving. Driver predictions based on this behavior can be combined with a user-estimated driver valuation metric for all driving events to generate an individualized driver prediction for a particular driving event.

Abstract: 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.

Abstract: According to some embodiments of the invention, movement measurements may be obtained from a movement sensor (e.g., an accelerometer) of a mobile device in a vehicle. In addition, location measurements may be obtained from a location sensor (e.g., a GPS) of the mobile device in the vehicle. The movement measurements and the location measurements may be cross-referenced to each other to remove erroneous measurements, such as physically impossible measurements. The remaining measurements may be used to draw conclusions about the movements or locations, such as to identify a movement event (e.g., a braking event, an acceleration event, or the like).

Abstract: 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 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, predicting, detecting, and reconstructing vehicle accidents.

Abstract: Embodiments of the present invention provide systems and methods for combining sensor data to measure vehicle movement. Embodiments may collect vehicle and driving data using sensors of a mobile device of a user, such as a location determination sensor and a movement determination sensor. In some embodiments, the data from the sensors may be combined to more accurately estimate vehicle movement, such as vehicle acceleration.

Abstract: Embodiments of the present invention meet this need and others by providing systems and methods for detecting and assessing distracted drivers. Embodiments collect vehicle and driving data using a mobile device of a user. In a particular embodiment, data collected using the mobile device is analyzed to determine when the user is engaging in distracted driving behavior.

Abstract: 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.

Abstract: A system for collecting vehicle data includes a mobile device comprising a plurality of sensors, a memory, and a processor coupled to the memory. The processor is configured to perform operations including obtaining a plurality of movement measurements from at least one of the plurality of sensors in the mobile device, determining a plurality of transportation modes using the plurality of movement measurements, and determining a mode transition using the plurality of transportation modes. The operations also include determining a transition probability using the mode transition. The operations further include creating a transition model using the transition probabilities, determining that the transition model indicates that a probability that the second transportation mode comprises driving is above a threshold, obtaining a plurality of driving movement measurements from at least one of the plurality of sensors, and determining the vehicle data using the driving movement measurements.

Abstract: Methods and systems are provided that enable accurate driving behavior data (e.g., vehicle acceleration data) to be obtained by a mobile device, despite the reference frames of the mobile device and the vehicle occasionally moving relative to each other. Accordingly, a user does not have to maintain a mobile device stationary relative to a vehicle in order to have a high likelihood that accurate driving data is collected.

Abstract: A mobile-device-based system for classifying a mode of transportation during a trip includes a mobile device including a location detection system and an accelerometer. The mobile device is configured to collect location data and acceleration data during the trip. The system also includes a data processing block configured to receive the location data from the mobile device, receive contextual data related to a plurality of transportation systems, and process the location data and at least a portion of the contextual data using a first transportation mode classifier associated with a first of the plurality of transportation systems and at least a second portion of the contextual data using a second transportation mode classifier associated with a second of the plurality of transportation systems. The data processing block is also configured to classify the mode of transportation during the trip and update the classifiers based on user input.

Abstract: A method of determining vehicle entry information for a user includes obtaining a yaw measurement using a mobile device, determining, using a processor, a first time span associated with a user entering a vehicle, and determining, using the processor, a second time span associated with a user exiting the vehicle. The method also includes determining that a change in magnitude over a portion of the yaw measurement is greater than a predetermined threshold over at least one of the first time span or the second time span and determining an angular change of the yaw measurement over the predetermined threshold. The method further includes associating right hand entry with the vehicle entry information if the angular orientation of the yaw measurement is clockwise and associating left hand entry with the vehicle entry information if the angular orientation of the yaw measurement is counter-clockwise.