Abstract: A sensor network comprises at least one lateral optical fiber and at least one longitudinal optical fiber. The lateral fiber comprises optical sensors coupled to a pavement in a transverse orientation relative to a direction of vehicle travel along the pavement. The longitudinal fiber comprises optical sensors coupled to the pavement in a longitudinal orientation relative to the direction of vehicle travel. The optical sensors are configured to produce wavelength shift signals comprising one or more lateral strain signals associated with the lateral fiber and one or more tangential strain signals associated with the longitudinal fiber. A processor is operatively coupled to the sensor network and configured to determine a weight of vehicles moving along the pavement based on the lateral and tangential strain signals. A transmitter is operatively coupled to the processor and configured to transmit the weight of vehicles to a predetermined location.

Abstract: The invention relates to a method and system for path planning of a wave glider, comprising acquiring historical navigation data of the glider and an underwater vehicle via a shore-based monitoring center; fitting historical navigation data nonlinearly by a deep learning neural network to obtain a trained network; acquiring real-time navigation data of the glider at an off-line end, real-time navigation data and predetermined shipping track data of the vehicle; obtaining the set of off-line optimized path planning schemes of the glider by the above data and the trained network; and determining an optimal path planning scheme of the glider by the deep learning neural network according to real-time data and constraint data of the glider at the on-line end. The invention can reasonably plan the path of the glider and ensure continuous and reliable information interaction between the glider and the vehicle.

Abstract: A deep-sea low-cost long-endurance collaborative navigation and positioning system. A shore-based monitoring center transmits a route planning solution to a wave glider. The wave glider follows an underwater vehicle to travel and feeds back state information of the wave glider and state information of the underwater vehicle to the shore-based monitoring center in real time. The shore-based monitoring center adjusts the route planning solution according to the state information in real time. The wave glider and the underwater vehicle are respectively equipped with an underwater acoustic communication machine.

Abstract: A deep-sea low-cost long-endurance collaborative navigation and positioning system. A shore-based monitoring center transmits a route planning solution to a wave glider. The wave glider follows an underwater vehicle to travel and feeds back state information of the wave glider and state information of the underwater vehicle to the shore-based monitoring center in real time. The shore-based monitoring center adjusts the route planning solution according to the state information in real time. The wave glider and the underwater vehicle are respectively equipped with an underwater acoustic communication machine.

Abstract: The invention relates to a method and system for path planning of a wave glider, comprising acquiring historical navigation data of the glider and an underwater vehicle via a shore-based monitoring center; fitting historical navigation data nonlinearly by a deep learning neural network to obtain a trained network; acquiring real-time navigation data of the glider at an off-line end, real-time navigation data and predetermined shipping track data of the vehicle; obtaining the set of off-line optimized path planning schemes of the glider by the above data and the trained network; and determining an optimal path planning scheme of the glider by the deep learning neural network according to real-time data and constraint data of the glider at the on-line end. The invention can reasonably plan the path of the glider and ensure continuous and reliable information interaction between the glider and the vehicle.