Abstract: A method of enhancing positioning of a moving vehicle based on visual identification of visual objects, comprising obtaining from a location sensor a global positioning and a movement vector of a moving vehicle, capturing one or more images using one or more imaging devices mounted on the moving vehicle to depict at least partial view of a surroundings of the moving vehicle, analyzing the image(s) to identify one or more visual objects having a known geographical position obtained according to the global positioning from a visual data record associated with a navigation map, analyzing the image(s) to calculate a relative positioning of the moving vehicle with respect to the identified visual object(s), calculating an enhanced positioning of the moving vehicle based on the relative positioning and applying the enhanced positioning to a navigation system of the moving vehicle.

Abstract: A computer-implemented method and apparatus for accurately determining a vehicle's position and predicting navigation key points in real time. The method including instructing a vehicle mounted camera to capture a plurality of images, computing the angular changes between a first image and a subsequent second image, determining the vehicle's position and heading vector from the computed angular changes, collecting at least one image of the plurality of images as a first training subset, obtaining image-related coordinates of navigation key points as a second training subset related to the at least one image of the first training data subset, supplying the first and second training data subset to an artificial neural network as a training dataset, and training the artificial neural network on the training dataset to predict image-related coordinates of navigation key points indicative of road sign locations and/or turn points.

Abstract: A method of enhancing positioning of a moving vehicle based on visual identification of visual objects, comprising obtaining from a location sensor a global positioning and a movement vector of a moving vehicle, capturing one or more images using one or more imaging devices mounted on the moving vehicle to depict at least partial view of a surroundings of the moving vehicle, analyzing the image(s) to identify one or more visual objects having a known geographical position obtained according to the global positioning from a visual data record associated with a navigation map, analyzing the image(s) to calculate a relative positioning of the moving vehicle with respect to the identified visual object(s), calculating an enhanced positioning of the moving vehicle based on the relative positioning and applying the enhanced positioning to a navigation system of the moving vehicle.

Abstract: A method of enhancing positioning of a moving vehicle based on visual identification of visual objects, comprising obtaining from a location sensor a global positioning and a movement vector of a moving vehicle, capturing one or more images using one or more imaging devices mounted on the moving vehicle to depict at least partial view of a surroundings of the moving vehicle, analyzing the image(s) to identify one or more visual objects having a known geographical position obtained according to the global positioning from a visual data record associated with a navigation map, analyzing the image(s) to calculate a relative positioning of the moving vehicle with respect to the identified visual object(s), calculating an enhanced positioning of the moving vehicle based on the relative positioning and applying the enhanced positioning to a navigation system of the moving vehicle.

Abstract: Embodiments are provided for determining driving behavior. In an example method for determining driver behavior from a driving session, the method includes obtaining sensor data from a sensor during a driving session, obtaining image data from an imaging device during the driving session, and analyzing at least one of the sensor data and the image data from the driving session, to identify an event of interest. The method further includes assigning a classification to the event of interest according to a correlation between the sensor data for the event of interest and at least one image from the image data for the event of interest, the correlation based on time the sensor data and the image data is obtained during the driving session, and, wherein the at least one image for the event of interest provides the context for the event of interest.

Abstract: A method of alerting a vehicle's driver. The method comprises receiving an azimuth value indicating a gazing direction of a head of the driver from a primary device placed on the driver, receiving a vehicle bearing value indicating a vehicle moving direction of the vehicle driven by the driver, calculating an angular difference between the azimuth value and the vehicle bearing value, generating an alert when the angular difference deviates from an angular threshold, and automatically presenting the alert to the driver in response to the angular difference.

Abstract: A system on chip (SoC) having an integrated circuit (IC) integrating into a single chip advance driver assistance systems (ADAS) processing unit(s), application processing unit(s), at least one memory storing ADAS code comprising ADAS computer instructions adapted to be executed on the ADAS processing unit(s) for processing vehicle sensor data and VM code for executing VM(s) on the application processing unit(s) and a hypervisor which manages an execution of at least one operation system of the VM(s) and an access to a processor shared memory of the ADAS processing unit(s) for acquiring an outcome of executing the ADAS computer instructions for the completion of an ADAS enhancing function by the execution of the VM(s) on the application processing unit(s).

Abstract: A method of calculating a commonly driven velocity recommendation, comprising: gathering a plurality of data messages from a plurality of client devices located in a plurality of different vehicles, each data message comprises a current location value, a current bearing value, and a current velocity value estimated for a hosting vehicle; clustering the plurality of data messages in a plurality of clusters by matching the respective location values and bearing values; calculating a commonly driven velocity per cluster of the plurality of clusters by combining data from respective cluster members; and retrieving the commonly driven velocity in response to an indication of a current location and a current bearing thereof which matches location and bearing of members of the respective cluster.

Abstract: A method of enhancing positioning of a moving vehicle based on visual identification of visual objects, comprising obtaining from a location sensor a global positioning and a movement vector of a moving vehicle, capturing one or more images using one or more imaging devices mounted on the moving vehicle to depict at least partial view of a surroundings of the moving vehicle, analyzing the image(s) to identify one or more visual objects having a known geographical position obtained according to the global positioning from a visual data record associated with a navigation map, analyzing the image(s) to calculate a relative positioning of the moving vehicle with respect to the identified visual object(s), calculating an enhanced positioning of the moving vehicle based on the relative positioning and applying the enhanced positioning to a navigation system of the moving vehicle.

Abstract: A method of alerting a vehicle's driver. The method comprises receiving an azimuth value indicating a gazing direction of a head of the driver from a primary device placed on the driver, receiving a vehicle bearing value indicating a vehicle moving direction of the vehicle driven by the driver, calculating an angular difference between the azimuth value and the vehicle bearing value, generating an alert when the angular difference deviates from an angular threshold, and automatically presenting the alert to the driver in response to the angular difference.

Abstract: A method of alerting a vehicle's driver. The method comprises receiving an azimuth value indicating a gazing direction of a head of the driver from a primary device placed on the driver, receiving a vehicle bearing value indicating a vehicle moving direction of the vehicle driven by the driver, calculating an angular difference between the azimuth value and the vehicle bearing value, generating an alert when the angular difference deviates from an angular threshold, and automatically presenting the alert to the driver in response to the angular difference.

Abstract: A system on chip (SoC) having an integrated circuit (IC) integrating into a single chip advance driver assistance systems (ADAS) processing unit(s), application processing unit(s), at least one memory storing ADAS code comprising ADAS computer instructions adapted to be executed on the ADAS processing unit(s) for processing vehicle sensor data and VM code for executing VM(s) on the application processing unit(s) and a hypervisor which manages an execution of at least one operation system of the VM(s) and an access to a processor shared memory of the ADAS processing unit(s) for acquiring an outcome of executing the ADAS computer instructions for the completion of an ADAS enhancing function by the execution of the VM(s) on the application processing unit(s).

Abstract: A method of calculating a commonly driven velocity recommendation, comprising: gathering a plurality of data messages from a plurality of client devices located in a plurality of different vehicles, each data message comprises a current location value, a current bearing value, and a current velocity value estimated for a hosting vehicle; clustering the plurality of data messages in a plurality of clusters by matching the respective location values and bearing values; calculating a commonly driven velocity per cluster of the plurality of clusters by combining data from respective cluster members; and retrieving the commonly driven velocity in response to an indication of a current location and a current bearing thereof which matches location and bearing of members of the respective cluster.

Abstract: Embodiments are provided for determining driving behavior. In an example method for determining driver behavior from a driving session, the method includes obtaining sensor data from a sensor during a driving session, obtaining image data from an imaging device during the driving session, and analyzing at least one of the sensor data and the image data from the driving session, to identify an event of interest. The method further includes assigning a classification to the event of interest according to a correlation between the sensor data for the event of interest and at least one image from the image data for the event of interest, the correlation based on time the sensor data and the image data is obtained during the driving session, and, wherein the at least one image for the event of interest provides the context for the event of interest.

Abstract: A method of alerting a vehicle's driver. The method comprises receiving an azimuth value indicating a gazing direction of a head of the driver from a primary device placed on the driver, receiving a vehicle bearing value indicating a vehicle moving direction of the vehicle driven by the driver, calculating an angular difference between the azimuth value and the vehicle bearing value, generating an alert when the angular difference deviates from an angular threshold, and automatically presenting the alert to the driver in response to the angular difference.