Embodiments of the disclosure provide for identification of zones for transitioning a vehicle from a beyond visual line of sight (BVLOS) mode to a visual observer mode. Some embodiments receive a travel pathway for a vehicle and generate signal strength indications for the travel pathway based on the travel pathway and satellite-based positioning data from a remote computing environment. Some embodiments generate, based on the signal strength indications, a particular zone along the travel pathway associated with poor signal strength. Some embodiments generate, based on the signal strength indications and particular zone, a visual observer indication that indicates a position along the travel pathway at which a transition of the vehicle from a BVLOS mode to a visual observer mode is initiated. Some embodiments modify the travel pathway based on the visual observer indication and provide the modified travel pathway to a zone-remote control system that controls the vehicle.

An adaptive fuzzy integral differential line-of-sight (AFIDLOS) method for path tracking of a laser bathymetry unmanned surface vehicle is provided. The AFIDLOS method includes determining an AFIDLOS manner, establishing an unmanned surface vehicle control model, determining an LQR heading controller, and determining a path tracking manner by combining the AFIDLOS manner and the LQR controller to realize a path tracking control of an unmanned surface vehicle in a microcontroller. The method for path tracking is verified in experiments. Experimental results show that, compared with a traditional LOS guidance rate, 79.85% reduction in overshoot, and 55.32% shorter adjustment time are achieved by the AFIDLOS manner in simulation experiments, while 9.5% of an average lateral error is reduced in the Beihai Beach experiment, and an overlap rate between strips reaches 30% in the Pinqing Lake experiment, which meets the accuracy requirements of bathymetric mapping.