Abstract: A method of operation of a navigation system includes: determining a geographic location, of a vehicle, while a global positioning location is blocked by an obstruction and the geographic location is from an in-vehicle location sensor in the vehicle; extracting an image line from a surrounding image with an artificial intelligence model and the surrounding image is from an in-vehicle image sensor in the vehicle; transforming an image coordinate of the image line to a world coordinate of a HD map local storage based on the geographic location; extracting a map line from the HD map local storage based on the world coordinate; determining a pose relationship between the image line and the map line paired as either horizontal or vertical; generating a map-related location for the vehicle based the geographic location and the pose relationship; and communicating the map-related location for displaying on a user interface.

Abstract: A navigation system includes: a control circuit configured to: generate a video clip by parsing an interval of a sensor data stream for a region of travel; analyze the video clip submitted to a deep learning model, already trained, including identifying a traffic flow estimate; access a position coordinate for calculating a distance to intersection; generate a traffic flow state by fusing a corrected speed, the traffic flow estimate, and the distance to intersection; merge a vehicle maneuvering instruction into the traffic flow state for maneuvering through the region of travel; and a communication circuit, coupled to the control circuit, configured to: communicate the traffic flow state for displaying on a device.

Abstract: A method of operation of a navigation system includes: determining a geographic location, of a vehicle, while a global positioning location is blocked by an obstruction and the geographic location is from an in-vehicle location sensor in the vehicle; extracting an image line from a surrounding image with an artificial intelligence model and the surrounding image is from an in-vehicle image sensor in the vehicle; transforming an image coordinate of the image line to a world coordinate of a HD map local storage based on the geographic location; extracting a map line from the HD map local storage based on the world coordinate; determining a pose relationship between the image line and the map line paired as either horizontal or vertical; generating a map-related location for the vehicle based the geographic location and the pose relationship; and communicating the map-related location for displaying on a user interface.

Abstract: A method of operation of a navigation system comprising: receiving multiple frames, including a first frame and a second frame, of images; detecting a traffic sign from the images between the first frame and the second frame based on a sign recognition model; extracting a first image from the first frame and a second image from the second frame; matching the traffic sign is the same in the first image and the second image based on a similarity model; generating a sign location of the traffic sign with an inertial measurement unit reading based on the first image and the second image; and generating a global coordinate for the sign location for displaying on a navigation map.

Abstract: A navigation system includes: a control circuit configured to: generate a video clip by parsing an interval of a sensor data stream for a region of travel; analyze the video clip submitted to a deep learning model, already trained, including identifying a traffic flow estimate; access a position coordinate for calculating a distance to intersection; generate a traffic flow state by fusing a corrected speed, the traffic flow estimate, and the distance to intersection; merge a vehicle maneuvering instruction into the traffic flow state for maneuvering through the region of travel; and a communication circuit, coupled to the control circuit, configured to: communicate the traffic flow state for displaying on a device.