A fiber optic sensing technology for vehicle run-off-road incident automatic detection by an indicator of sonic alert pattern (SNAP) vibration patterns. A machine learning method is employed and trained and evaluated against a variety of heterogeneous factors using controlled experiments, demonstrating applicability for future field deployment. Extracted events resulting from operation of our system may be advantageously incorporated into existing management systems for intelligent transportation and smart city applications, facilitating real-time alleviation of traffic congestion and/or providing a quick response rescue and clearance operation.

Structural component, in particular for a vehicle body, comprising a structural element (12) and a sensor arrangement (16), wherein the sensor arrangement (16) is connected to the structural element (12) and comprises at least one optical waveguide (14).

A fiber optic sensing technology for vehicle run-off-road incident automatic detection by an indicator of sonic alert pattern (SNAP) vibration patterns. A machine learning method is employed and trained and evaluated against a variety of heterogeneous factors using controlled experiments, demonstrating applicability for future field deployment. Extracted events resulting from operation of our system may be advantageously incorporated into existing management systems for intelligent transportation and smart city applications, facilitating real-time alleviation of traffic congestion and/or providing a quick response rescue and clearance operation.

A floodwater risk assessment system for a vehicle includes one or more cameras oriented to collect image data of floodwater located along a roadway the vehicle is traveling along, a time-of-flight sensor system that directs a laser beam towards a plurality of target points disposed along the floodwater one or more controllers in electronic communication with the one or more cameras and the time-of-flight sensor system. The one or more controllers execute instructions to determine a risk associated with crossing the floodwater at each of the plurality of target points located along the floodwater based on a flow speed of the floodwater and a floodwater depth. The one or more controllers generate a notification indicating the risk associated with crossing the floodwater at the plurality of target points located along the floodwater.

A floodwater risk assessment system for a vehicle includes one or more cameras oriented to collect image data of floodwater located along a roadway the vehicle is traveling along, a time-of-flight sensor system that directs a laser beam towards a plurality of target points disposed along the floodwater one or more controllers in electronic communication with the one or more cameras and the time-of-flight sensor system. The one or more controllers execute instructions to determine a risk associated with crossing the floodwater at each of the plurality of target points located along the floodwater based on a flow speed of the floodwater and a floodwater depth. The one or more controllers generate a notification indicating the risk associated with crossing the floodwater at the plurality of target points located along the floodwater.

The present application generally relates to systems and methods for a fiber-optic gyroscope on an autonomous vehicle. The autonomous vehicle includes a fiber-optic gyroscope. The fiber-optic gyroscope includes at least one fiber-optic cable loop integrated into a structure of the autonomous vehicle. The autonomous vehicle further includes an autonomy computing system comprising at least one processor coupled to the fiber-optic gyroscope and at least one memory device storing computer. The processor is configured to receive sensor data from the fiber-optic gyroscope and compute a heading for an autonomous vehicle based on the sensor data.