53 results about "Collision avoidance system" patented technology

A vehicular driving assist system includes a sensor disposed at a vehicle. The vehicular driving assist system is operable to at least partially control the equipped vehicle as the equipped vehicle moves in a direction of travel. As the equipped vehicle moves in the direction of travel, and based on processing captured sensor data, the vehicular driving assist system determines a following vehicle at least rearward of the equipped vehicle and travelling in the direction of travel. With the determined following vehicle at least rearward of the equipped vehicle, and based on determination of a potential forward braking event relative to a road condition at least forward of the equipped vehicle, the vehicular driving assist system adjusts control of the equipped vehicle to commence reducing speed of the equipped vehicle at a distance relative to the determined road condition greater than when no following vehicle is determined.

The disclosed technology teaches a system and method for providing driver assistance alerts to a driver using an end-to-end artificial intelligence advanced driver assistance system. The disclosed techniques further include receiving a series of environmental data of a driving state including at least video from a camera, return data from an optical sensor, and location data from a GNSS receiver, where the camera, the optical sensor, and the GNSS receiver are coupled to a processor carried by a vehicle; processing the environmental data as input to an end-to-end neural network, wherein the end-to-end neural network is trained to generate specified steering and speed control actions in response to a current driving state; analyzing hidden layer data and output data from the end-to-end neural network to estimate collision avoidance data; and presenting to the driver a user interface including a driver assistance alert based on the collision avoidance data.

This invention relates to the field of ship collision avoidance technology, and discloses an intelligent active collision avoidance system and method for ships. The system includes a sensing module, a control and decision-making module, and an execution module. The sensing module collects distance, outline, and micro-motion data of obstacles around the ship. The control and decision-making module identifies impending collision threats and predicts the timing of a collision based on the data, generating an airbag trigger response strategy that matches the timing of the collision. The modular airbag unit of the execution module is normally flat and close to the hull, and can rapidly inflate to a preset shape before a collision, forming a buffer protection structure adapted to the collision intensity. This invention achieves proactive, intelligent, and precise ship collision avoidance. The buffer performance can dynamically adapt to the collision intensity, and the modular design facilitates maintenance and expansion, significantly improving collision safety and navigation economy in scenarios such as berthing and unberthing.

The invention belongs to the technical field of anti-impact protection. According to the snail shell imitating square tube improved anti-impact energy absorption structure and the application, the structural monomers or the structural modular array can be used for dynamic load protection. Under the action of an axial compression load, the structure realizes a multi-layer and progressive collapse path, and has low initial peak crushing force and staged and approximately linear increasing force-displacement response characteristics. According to the bionic structure, the energy absorption efficiency of the rectangular pipe is effectively improved under the condition that the mass and the manufacturing complexity are not increased, and the bionic structure is suitable for vehicle anti-collision systems, rail transit buffer devices and other anti-impact protection fields.

A vehicle steering automatic collision avoidance system includes a driving control computer connected to an autonomous emergency braking assistance system and an automobile steering automatic collision avoidance system. The autonomous emergency braking assistance system is configured to provide autonomous emergency braking assistance information. The vehicle steering automatic collision avoidance system is configured to provide steering collision-avoidance decision information, when activated. The driving control computer is capable of integrating the autonomous emergency braking assistance information and the steering collision-avoidance decision information.

A proximity detection and collision avoidance system determines whether a collision risk exists between two vehicles by measuring magnetic field vectors generated on each of the vehicles as the relative distance between the vehicles decreases.

Methods and systems are provided for autonomous vehicle operation for collision avoidance. One method involves identifying an autonomous operating mode and one or more settings associated with the autonomous operating mode prior to entering an autonomous collision avoidance mode in response to an output from a collision avoidance system, and after entering the autonomous collision avoidance mode, automatically restoring autonomous operation upon deactivation of the autonomous collision avoidance mode. For example, the autonomous operating mode may be automatically reinitiated based on the current vehicle status using the one or more settings in response to deactivation of the autonomous collision avoidance mode when it is determined that the autonomous operating mode is viable based on a relationship between a current vehicle status and the one or more settings associated with the autonomous operating mode.

This invention discloses a collision avoidance method and system for a de-hooking robot under complex working conditions. The invention relates to the technical field of collision avoidance methods. Based on the working area, the type of complex working condition, and the de-hooking robot, multiple de-hooking positions are determined within the working area. The de-hooking behavior of the robot at each de-hooking position is determined based on the current image corresponding to each de-hooking position and the robot's working mode. The collision area of ​​the de-hooking robot is predicted based on each de-hooking behavior and the current image corresponding to each de-hooking position. Multiple collision nodes are determined based on the identification of the collision areas. An optimized de-hooking behavior is determined based on the multiple collision nodes, the corresponding de-hooking behavior, and the robot's posture. Finally, a collision avoidance system for the de-hooking robot is determined based on the optimized de-hooking behavior, the original de-hooking behavior, and the robot's movement path, thus improving the accuracy of the collision avoidance system.

The utility model relates to the technical field of navigation, in particular to a ship collision avoidance navigation system with a dynamic obstacle recognition function, which comprises a solid-state laser radar, a millimeter-wave radar, a visual sensor, an AIS (automatic identification system) receiver, a GNSS (global navigation satellite system) receiver, an inertial measurement unit and a central processing unit. According to the utility model, a plurality of advanced sensors and control modules are integrated on a hardware level, so that an intelligent collision avoidance system which is high in precision and integrates all-weather and all-time sensing and decision-making capabilities is constructed.

The invention discloses a vision and laser dual-redundancy anti-collision system and an anti-collision method, and relates to the technical field of crane anti-collision, the vision and laser dual-redundancy anti-collision system comprises a data acquisition layer and a data processing layer, the data acquisition layer comprises a plurality of laser radars and industrial cameras, the laser radars acquire three-dimensional point cloud data, and the industrial cameras acquire picture information of multiple visual angles; the data processing layer comprises a camera network, a laser radar network and a 3D detector, the camera network extracts a first feature from the picture information, the first feature comprises a multi-view two-dimensional feature and a multi-view inference-based three-dimensional feature, the laser radar network extracts a second feature from the point cloud data, and the second feature comprises a three-dimensional structure feature; the first feature and the second feature are fused and then input into a 3D detector, and the 3D detector identifies target information and performs system control and / or early warning based on the identified target information. The effects of accurately detecting the moving speed and the moving direction of the moving target and avoiding the obstacle are achieved.

A collision avoidance system (CAS) airborne unit onboard an aerial platform of a first priority level includes a navigational module to determine current position of the aerial platform; a communication module to intermittently transmit a localization transmission, and to receive intermittently transmitted localization transmissions from another CAS airborne unit on-board another lower priority level aerial platform; and a processor to calculate, based on the received intermittently transmitted localization transmissions and on a current location, speed and heading of the CAS airborne unit, a collision risk between the aerial platform and the other aerial platform, and to generate one or a plurality of steering commands and cause a transmission of one or a plurality of a steering commands to be performed by the other aerial platform and to cause the steering commands to be transmitted by the communication module to the other CAS airborne unit.

A working machine includes a body, a ground engaging propulsion structure supporting the body, a working arm, a control system, and a collision avoidance system. The collision avoidance system has a camera configured to monitor an area in its field of view and to generate an output signal to the control system in response to a detected animate object. The control system includes a processor configured to execute a machine learning algorithm trained to determine whether the detected object is an animate object to determine whether an animate object is within the field of view. The system provides an output to alert an operator of the working machine if it is determined that an animate object has been detected in the field of view of the at least one camera.

Low power and / or low footprint optical communication technologies that support short to medium range exoatmospheric communications and provide bidirectional communication with nearly spherical coverage.

Techniques are disclosed for reducing false positives for generating warnings to avoid potential collisions between a vehicle and vulnerable road users (VRUs). This is accomplished via an onboard vehicle safety system that uses crowdsourced map data to determine whether a vehicle is capable of performing a maneuver that results in a lateral shift of the vehicle (which may include a lane-shifting or turning maneuver) within a predetermined threshold time period. The ability for the vehicle to make the turning maneuver, among other driving scenarios, may be used to by the safety system to intelligently determine whether a warning or other action is needed to avoid a potential collision with a VRU. In this way, the occurrence and number of false warnings / interventions are minimized or at least reduced, leading to more attentive drivers and thereby improving VRU safety.

A method for operating a modular robot including a first module and a second module is provided. The first module includes a first controller, and the first controller includes a first failsafe position detection for a movable element of the first module. The method includes controlling the second module, which includes detecting a first position of movable elements via a first single position detector. A second position of the movable elements is detected via a second position detector, which is configured as a position probe that is attachable to the at least one movable element of the second module. The second position is combined with the first position to form a second failsafe position detection. The first failsafe position detection is combined with the second failsafe position detection to form a combined failsafe position detection for the modular robot.

This incorporates a vehicle control device that suppresses unnecessary activation of a collision avoidance system caused by a drop in target information acquisition accuracy when a host vehicle is cornering. A vehicle control device 100 comprises: a rotational speed sensing unit 102, which detects the rotational speed of a vehicle 400; a vehicle speed sensing unit 104, which detects the speed of the vehicle 400; a target position sensing unit 1101, which detects the position of a target 301 detected by an external environment sensing unit 101 integrated into the vehicle 400; and a target base speed calculation unit 1104, which detects the base speed of the target 301 detected by the external environment sensing unit 101.a reference target baseline speed error calculation unit 114, which detects a baseline speed error of a reference target 404, which serves as a reference outside the vehicle 400; a driver assistance function calculation unit 115, which receives the execution content of a driver assistance function related to the safety of the vehicle against a moving object detected by the external environment detection unit 101, using the baseline speed error of the reference target 404; and an output unit 116, which outputs a control instruction to execute the driver assistance function to driver assistance function execution units 105 and 106 of the vehicle 400 based on the received execution content.

An onboard computing system of an ownship vehicle comprising processing circuitry configured to: determine a presence of an obstacle in a planned route for the ownship vehicle; determine a avoidance route for the obstacle; transmit the avoidance route to an external computing system; determine whether the onboard computing system is in communication with the external computing system; in response to a determination that the onboard computing system is in communication with the external computing system, cause the ownship vehicle to avoid the obstacle based on information received via the communications circuitry from the external computing system; and in response to a determination that the onboard computing system is not in communication with the external computing system, cause the ownship vehicle to proceed along the avoidance route, the avoidance route comprising a change to a vertical component of the planned route.

The invention provides an unmanned aerial vehicle formation keeping, transformation, obstacle avoidance and collision avoidance system based on an artificial potential field method. The system comprises a formation structure module, a parameter measurement and calculation module, an artificial potential field module and an instruction integration module. The formation modeling module is used for performing virtual modeling on the formation through a virtual structure method, giving a target position of the current unmanned aerial vehicle, calculating a relative position and a relative speed with the target position according to the target position, calculating each obstacle according to the obstacle information, setting an emergency degree for the obstacles, and determining the formation according to the emergency degree. And calculating the gravitation and the repulsive force of the target position and the obstacle, finally synthesizing an initial resultant force, limiting the resultant force, and finally outputting a control instruction which can be actually executed by the optimized unmanned aerial vehicle. According to the method, the overall stability of the formation is ensured, flexible and efficient formation change can be realized, and real-time and reliable obstacle avoidance and collision avoidance capabilities are realized, so that the autonomous collaborative operation level of a multi-unmanned aerial vehicle system in a complex environment is improved.

The utility model provides a vehicle anti-collision system and a vehicle. The vehicle anti-collision system comprises a first laser communication box, a vehicle control unit and a vehicle speed adjustment executing mechanism. The first laser communication box comprises a laser transceiver module, an optical module and a control module; the first laser communication box is mounted at the top of a vehicle; the laser transceiver module is connected with the optical module, and the optical module is connected with the control module; the first laser communication box is connected with the vehicle control unit through the control module, and the vehicle control unit is connected with the vehicle speed adjustment executing mechanism. Thus, the laser communication box is installed on the top of the vehicle, and the speed of the front vehicle can be accurately obtained in time based on the characteristics that laser transmission is high in transmission speed, small in delay and small in influence of factors such as severe weather and sunlight; therefore, the vehicle speed is adjusted according to the vehicle speed so as to reduce the collision risk and guarantee the driving safety.

Method for operating a collision avoidance system (3) of a vehicle (1), wherein, depending on a collision-critical situation, an intervention strategy for reducing the severity of a detected collision imminent between the vehicle (1) and a collision object is determined, and depending on a predicted collision angle (α) between a motion vector (B1) of the vehicle (1) and another motion vector (B2) of the collision object at a predicted collision time, a distinction is made between an intervention strategy for accident reduction, an intervention strategy for the time of collision, and an intervention strategy for rear-end collision. wherein, after determining the decision strategy by means of the collision avoidance system (3), an emergency braking function or an emergency evasive maneuver function is activated depending on a determined overlap area between the vehicle (1) and the collision object at the predicted collision time, and wherein a decision to perform automatic emergency braking or automatic emergency evasive maneuvers is made depending on a predetermined threshold value with respect to the critical overlap area between the vehicle (1) and the collision object at the predicted collision time. characterized in that a critical overlap area is determined for each intervention strategy, from which point onwards, despite initiated emergency braking, the collision between the vehicle (1) and the collision object is unavoidable and that if it is determined that the threshold value with respect to the critical overlap area per intervention strategy is undershot, the emergency avoidance function of the vehicle (1) is activated.

A vehicle is configured to be positioned upstream of traffic relative to a scene to protect personnel responding to the scene. The vehicle includes a collision avoidance and mitigation system configured to alert personnel on the scene of a threat caused by an approaching vehicle and / or alert the driver of the approaching vehicle of the scene. The collision avoidance and mitigation system is configured to determine a threat score based on a past trajectory of a detected vehicle and a number of previously observed trajectories of vehicles approaching the scene. The collision avoidance system can generate a threat score for the detected vehicle and adjust the threat score based on a comparison of the past trajectory to the number of previously observed trajectories. An alert signal is generated responsive to the threat score exceeding a threshold.

The present invention provides an improved collision avoidance device that can avoid a collision through automatic braking even if there is a risk of the vehicle colliding with an obstacle again after the automatic braking has ended. [Solution] A vehicle collision avoidance device 100 includes a driver assistance ECU 10, which is configured as a control unit that, based on the detection results of a target information acquisition device 18 as a target detection device, determines that there is a risk of the vehicle 102 colliding with an obstacle, and performs automatic braking to reduce the risk, wherein the driver assistance ECU 10 determines whether a specific condition is met, such that the accelerator opening due to the driver's driving operation is equal to or greater than a reference opening, when the automatic braking is completed, and when it is determined that the specific condition is met, it is configured to control the driving force of the vehicle so that the vehicle speed does not exceed the upper limit of the vehicle speed range in which automatic braking is performed.

A collision determination apparatus is provided. The collision determination apparatus is provided with an acquiring unit that acquires a posture and movement characteristics of an object to be determined whether a collision risk is present; and a reliability determination unit that determines a reliability of the movement characteristics using the posture and the movement characteristics acquired by the acquiring unit.

An airport collision avoidance system may include a tow vehicle configured to move an aircraft, the tow vehicle having a first beacon. The airport collision avoidance system may include at least one second beacon associated with at least one object. The airport collision avoidance system may include one or more processing circuits including one or more processors and one or more memories having instructions stored thereon that, when executed by the one or more processors, cause the one or more processors to: form a mesh network connection between the first beacon and the at least one second beacon; identify relative positionings between the tow vehicle, the aircraft, and the at least one object based on the mesh network connection; and at least partially control the tow vehicle based on the relative positionings between the tow vehicle, the aircraft, and the at least one object.

A vehicle collision avoidance system includes a collision sensor that generates a collision signal indicative of an object in a path of travel of the vehicle. A controller identifies a first side of the vehicle containing a blind spot for an operator of the vehicle. The controller further identifies a potential collision between the vehicle and the object responsive to the collision sensor and the speed of the vehicle and the trajectory of the vehicle. The controller suppresses, or adjusts one or more conditions for, generation of a control signal relating to the potential collision if the vehicle speed and trajectory meet predetermined conditions and the potential collision would occur on a second side of the vehicle opposite the first side of the vehicle.

To provide a proximity warning system that is less susceptible to noise generated from the power source of mobile equipment. [Solution] This proximity warning system detects the proximity of at least two mobile devices 1A and 1B and outputs a proximity warning. Each mobile device 1A and 1B is equipped with a master unit and a slave unit capable of UWB communication. The master unit includes a UWB communication unit, an alarm unit and a control unit. The control unit acquires information regarding the distance between the mobile devices 1A and 1B obtained through UWB communication between the master unit of the mobile device 1A equipped with the control unit and the slave unit of the other mobile device 1B, and outputs a proximity warning from the alarm unit when the distance is less than or equal to a predetermined value.