Abstract: A navigation system includes: a control circuit configured to: a control circuit configured to: capture a sensor data stream provided by optical sensors, extract lane lines from the sensor data stream, optimize an extrinsic parameter and an intrinsic parameter based on the extract of the lane lines, and compile optimized parameters including the extrinsic parameter and the intrinsic parameter; and a communication circuit, coupled to the control circuit, configured to receive an optical sensor alert for displaying on a device.

Abstract: A navigation system includes: a control circuit configured to: a control circuit configured to: capture a semantic frame from a sensor data stream for a region of interest, calculate a score (EQ1) for semantic points in the semantic frame, align the semantic points includes a pose error corrected, generate a semantic grid map of the semantic points including a high-level grid and a low-level grid, calculate grid map statistics by counting the semantic points in the low-level grid within the high-level grid, filter the semantic points in the low-level grid based on the grid map statistics of the high-level grid, and generate a semantic map from the low-level grid filtered and the high-level grid; and a communication circuit, coupled to the control circuit, configured to: process the semantic frame through a network, and process the semantic map through the network for displaying on a device.

Abstract: A navigation system includes: a control circuit configured to: a control circuit configured to: capture a semantic frame from a sensor data stream for a region of interest, crop an outer peripheral edge of the semantic frame by removing semantic points beyond the outer peripheral edge, calculate a world coordinate point cloud by calculating a global positioning system (GPS) location of the semantic points includes a pose error corrected, establish a probability value for a base-level grid, generate a semantic grid map by identifying a dominant percentage of the probability value of the base-level grid and an upper-level grid, and generate a semantic map from the semantic grid map to represent the region of interest; and; and a communication circuit, coupled to the control circuit, configured to transmit the semantic map for displaying on a device.

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 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.