A transport system for transporting workpieces includes a plurality of objects disposed along a path of travel and a driverless transport vehicle having a workpiece holder and a personal protection sensor such as a laser scanner. The sensor has a transmitter for generating detection radiation and a receiver adapted to receive detection radiation generated by the transmitter and reflected from persons or objects located in a monitoring area that is monitored by the detection radiation. A control device steers the transport vehicle along the travel path so that it does not collide with the objects and triggers a safety measure if the personal protection sensor has detected a person in the monitoring area. The objects support a coating or cladding that absorbs detection radiation impinging thereon or reflects it in such a direction that it cannot reach the receiver. As a result, the objects become invisible to the personal protection sensor and cannot trigger any safety measures.

A control unit performs a travel stop process for stopping travel of a travel unit in response to an indicator detection unit detecting a stop notice indicator section and then detecting a stop position indicator section. After the travel of the travel unit is stopped as a result of the travel stop process, the control unit performs a transfer process for causing a transfer unit to transfer an article. The control unit performs, instead of the transfer process, anomaly notification processing for providing a notification of an occurrence of an anomaly to a superordinate control unit, after the travel of the travel unit is stopped by the travel stop process, in response to: (i) a travel distance, from a position at which the indicator detection unit has detected the stop notice indicator section, being smaller than a determination distance smaller than a notice distance, and (ii) the indicator detection unit detecting the stop position indicator section.

An electronic device for stopping a vehicle can be activated automatically in the presence of an emergency stopping instruction. A module calculates at least one automatic movement setpoint of the vehicle in order to follow an emergency stopping trajectory comprising a plurality of successive emergency stopping vectors each associated with a separate segment of a portion of the successive segments of the predefined trajectory, from at least for each emergency stopping vector: a stored last actual movement vector of the autonomous vehicle, the predefined movement trajectory of the autonomous vehicle, and a stored last location datum of the autonomous vehicle, and delivered by at least one sensor of the autonomous vehicle. An emergency steering module is capable of steering the vehicle according to said at least one setpoint.

A method, computer program product, and computing system for operating an autonomous vehicle; monitoring the operation of a plurality of computing devices within the autonomous vehicle; and in response to detecting the failure of one or more of the plurality of computing devices, switching the autonomous vehicle from a nominal autonomous operational mode to a degraded autonomous operational mode.

A method for training control software to reinforce safety constraints using visual inputs includes performing template matching for each object in an image of a reinforcement learning (RL) agent's action space using a visual template for each object wherein each object in the RL agent's action space is detected, mapping each detected object to a set of planar coordinates for each object in the RL agent's action space, determining a set of safe actions for the RL agent by applying a safety specification for the RL agent's action space to the set of variables for coordinates for each object in the RL agent's action space, outputting the set of safe actions to the RL agent for a current state of a RL procedure, and preventing the RL agent from executing an action that is unsafe, before the RL agent takes an action.

A computer, including a processor and a memory, the memory including instructions to be executed by the processor to acquire one or more images from a camera and determine first camera noise values based on the one or more images by determining reactions of camera photo receptors to light. The instructions can include further instructions to compare the first camera noise values with second camera noise values determined based on previously acquired images from the camera and output a tamper determination for the camera based on whether the first camera noise values match, within a tolerance value, the second camera noise values determined based on the previously acquired images from the camera.

A marine vessel propulsion control system that smoothly performs propulsion control of a marine vessel includes a controller configured or programmed to control a propulsion device that applies a thrust to a marine vessel. The controller is configured or programmed to adjust the thrust based on position information of the marine vessel and map information that includes an avoidance target.

A work system includes an operation device that transmits an operation signal, a work machine that operates on the basis of the operation signal, and a transport vehicle that outputs a traveling control signal in a case where a fault in communication between the operation device and the work machine occurs.

A method for controlling the actuation of an actuatable restraint to help protect a vehicle occupant in response to a rollover event is implemented in a controller of a vehicle safety system that includes the actuatable restraint. To implement the method, the controller is configured to execute a roll discrimination metric that discriminates the occurrence of a ramp rollover event or an embankment rollover event in response to a vehicle roll rate (R_RATE) having a magnitude that exceeds a predetermined threshold roll rate (R_RATE). The controller is also configured to execute a switching metric that is operative to reduce the predetermined threshold roll rate (R_RATE) in response to a vehicle pitch rate (P_RATE) having a magnitude that exceeds a predetermined threshold pitch rate (P_RATE).

The present disclosure generally relates to generating emergency vehicle warnings, automatic control of autonomous vehicles based upon the emergency vehicle warnings. More particularly, the present disclosure relates to generating data representative of emergency vehicle warnings and alternate autonomous vehicle routing based upon real-time information related to an emergency vehicle. The information related to the emergency vehicle may include emergency vehicle origination location data, emergency vehicle current location data, emergency vehicle route data, and/or emergency vehicle destination location data. An emergency vehicle warning and/or alternate vehicle routing for autonomous vehicles may be generated based further on information related to an autonomous vehicle. In one aspect, an emergency vehicle may wirelessly communicate with the autonomous vehicle and/or an insurance provider remote server. The insurance provider may adjust auto insurance for insured individuals, having vehicles with the vehicle safety functionality discussed herein, to reflect lower risk and provide insurance savings to customers.