Exemplary embodiments described in this disclosure are generally directed to systems and methods for predicting a travel destination of an automobile based at least in part on identifying a category of an attire worn by an individual who is an occupant of the automobile or is moving towards the automobile with the intention of entering the vehicle. The attire may be one of various categories such as a business attire category, a business-casual attire category, a casual attire category, or a social attire category. The travel destination may be additionally predicted based on other factors such as an attire worn by a co-occupant of the automobile and historical data associated with the occupant and/or the co-occupant. The historical data may include a record of times at which the occupant traveled to a particular destination and the attire worn by the occupant when traveling to the destination.

A traffic flux maximization method and system to control traffic flow by combining classical computing machine learning to predict traffic flux minimization before its occurrence, with quantum annealing to optimize future positions of vehicles. Vehicles are redirected to minimize the travel time for each vehicle, taking into account other vehicles in the road network.

A method and/or system is able to improve vehicle safety by determining if an object is embedded in a tire of the vehicle. Audio data is received from a microphone that is positioned to capture sounds of the tire moving on the road. The speed of the vehicle is also obtained, where the speed overlaps the same timeframe of when the sounds of the tire are captured by the microphone. An object is determined to be embedded in the tire based on a frequency analysis of the received audio data relative to the speed of the vehicle. And an alert is output to the driver of the vehicle indicating that the object is embedded in the tire.

A system for tracking cumulative motor vehicle risk includes a satellite navigation system receiver disposed within a motor vehicle and configured to determine a present location of the motor vehicle. A computer processor receives the determined present location of the motor vehicle from the satellite navigation system receiver and generates a traveled route therefrom. A first computer server receives a plurality of motor vehicle claims records, determines a plurality of motor vehicle accident locations from the plurality of motor vehicle claims records, and generates a motor vehicle accident heat map from the plurality of motor vehicle accident locations. A second computer server determines a cumulative risk exposure of the motor vehicle based on the generated traveled route and the generated motor vehicle accident heat map.

A method and/or system is able to provide driver fingerprint via metadata extraction managed by a driver rating (DR) model trained by a machine learning center (MLC) coupled to a cloud based network (CBN). In one embodiment, a DR system includes a set of outward facing cameras, a set of inward facing cameras, and a vehicle onboard computer (VOC). The set of outward facing cameras mounted on a vehicle is used to collect external images representing a surrounding environment in which the vehicle operates. The set of inward facing cameras mounted in the vehicle is used to collect internal images including operator body expression representing at least operator's attention. The VOC is configured to determine the identity of operator and current operating style in response to the collected internal images, the collected external images, and historical stored data.

In some implementations, a mobile device can transmit traffic information to a server for analysis. The traffic information can include movement information including detected stops and durations of detected stops. The traffic information can be analyzed to detect traffic patterns that indicate locations of stop signs and/or stop lights. The traffic information can be analyzed to determine durations of stops at stop signs and/or stop lights. The durations of stops can be associated with a time of day and/or day of the week. In some implementations, navigational routes can be determined based stop sign and/or stop light information, including the delays attributable to detected stop signs and/or stop lights.

To statistically analyze information on the path of ra movement of a moving body. An information analysis device includes a communication unit that receives position information for a vehicle, a memory unit that stores map information pertaining to roads over which the vehicle can travel and position information concerning facilities, a visit frequency calculator that calculates the frequency at which the vehicle visits a facility on the basis of facility information concerning the facility, and a travel path specification unit that specifies the vehicle that has made a plurality of visits to the facility on the basis of the results of calculations made by the visit frequency calculator and specifies the travel path to the facility for the specified vehicle from the position information and the map information pertaining to the roads.

A method or system is able to refine Global Positioning System (GPS) information for guiding a vehicle via extracted metadata using a GPS refinement (GR) model managed by a virtuous cycle containing sensors, machine learning center (MLC), and a cloud based network (CBN). The GR system includes a set of outward facing cameras, a vehicle onboard computer (VOC), and GR model. The outward facing cameras mounted on a vehicle are capable of collecting external images representing a surrounding environment in which the vehicle operates. The VOC is configured to generate a positional vehicle location with respect to the surrounding environment in accordance with the external images and historical stored data obtained from CBN. The GR model is configured to generate a driving guidance based on combined information between the positional vehicle location and GPS data.

A navigation system and various methods of using the system are described herein. Search query results are refined by the system and are prioritized based at least in part upon sub-search categories selected during the searching process. Sub-searches can be represented by graphical icons displayed on the user interface.

Provided are a method and a system for controlling at least one feature of a vehicle based on a destination predicted when a driver of the vehicle does not input a specific destination to a navigation system of the vehicle. A driving pattern is determined using driving information of a vehicle. A driving model corresponding to the driving pattern among pre-stored driving models is determined. A destination of the determined driving model is identified as a prediction destination. Control signal corresponding to the prediction destination for controlling at least one feature of the vehicle is generated for performing a vehicle operation according to the vehicle control information.