Abstract: A vehicle system recognizes a situation of surroundings of a host vehicle, automatically controls at least steering of the host vehicle on the basis of the recognized situation of the surroundings to cause the host vehicle to perform lane change, acquires information on a route from a navigation device guiding the route along which the host vehicle travels, and suppresses control for assisting the steering on the basis of an event regarding the route when the event occurs in the navigation device.

Abstract: An autonomous platform can obtain sensor data descriptive of an actor in an environment of an autonomous vehicle and at least a portion of the environment of the autonomous vehicle that does not include the actor, the sensor data comprising at least one sweep of the environment of the autonomous vehicle; process the sensor data with a machine-learned perception model to generate a detection of the actor and one or more predicted future velocities; and determine a motion trajectory for the autonomous vehicle based at least in part on the detection and the one or more predicted future velocities.

Abstract: The invention relates to a system for assisting with driving a vehicle, including at least one sensor configured to detect the presence of an object in an environment outside the vehicle, at least one camera configured to acquire images of the environment outside the vehicle and to detect the presence of the object in the environment outside the vehicle. The at least one sensor detects at least one free space in the environment outside the vehicle, the at least one camera, on the basis of the acquired images, detects at least one free space. An electronic control unit configured to select a free space found by the at least one sensor and/or the at least one camera, the electronic control unit activates the display of images in the selected free space so as to indicate a new path to be followed by the vehicle.

Abstract: A method for operating an automated vehicle involves recording traffic congestion ahead of the vehicle and determining whether hazard lights of a vehicle following the vehicle in its lane are switched on. When the hazard lights of the following vehicle are switched on, a rear collision risk is evaluated as being lower than when the hazard lights are switched off.

Abstract: Systems, methods, and other embodiments described herein relate to a multi-task model that integrates recurrent models to improve handling of multi-sweep inputs. In one embodiment, a method includes acquiring sensor data from multiple modalities. The method includes separately encoding respective segments of the sensor data according to an associated one of the different modalities to form encoded features using separate encoders of a network. The method includes accumulating, in a detector, sparse features associated with sparse sensor inputs of the multiple modalities to densify the sparse features into dense features. The method includes providing observations according to the encoded features and the sparse features using the network.

Abstract: A vehicle control apparatus includes one or more processors. The one or more processors execute determination as to whether a driving state of the vehicle involves difficulty in continuing the automatic driving. In a case where the driving state is determined as involving difficulty in continuing the automatic driving, the one or more processors execute determination on a difficulty level of operation authority transfer from the automatic driving to the manual driving on the basis of information regarding a surrounding environment of the vehicle, information regarding a driving skill of a driver, and information regarding an experience level of the driver of the operation authority transfer. The one or more processors execute setting of a driving-state condition for executing the operation authority transfer in accordance with the difficulty level. The one or more processors execute the operation authority transfer in a case where the driving-state condition is satisfied.

Abstract: A laser diode firing circuit for a light detection and ranging (LIDAR) device that includes an inductively coupled feedback system is disclosed. The firing circuit includes a laser diode coupled in series with a transistor, such that current through the laser diode is controlled by the transistor. The laser diode is configured to emit a pulse of light in response to current flowing through the laser diode. A feedback loop is positioned to be inductively coupled to a current path of the firing circuit that includes the laser diode. As such, a change in current flowing through the laser diode induces a voltage in the feedback loop. A change in voltage across the leads of the feedback loop can be detected and the timing of the voltage change can be used to determine the time that current begins flowing through the laser diode.

Abstract: Example embodiments relate to techniques for adjusting vehicle behavior based on estimated unintentional lateral movements. A computing system may receive sensor data representing a truck's environment as the truck pulls a trailer and navigates above a threshold speed on a freeway or another type of road. The computing system may use the sensor data to detect another truck navigating in an adjacent lane and at a speed that indicates an increased likelihood of a pass maneuver occurring between the trucks. Responsive to determining the increased likelihood of the pass maneuver occurring between the vehicles, the computing system may estimate an unintentional lateral movement for the pass maneuver based on parameters that can include the truck's speed, the size of the other truck's trailer, and a wind condition of the environment. The computing system can subsequently control the truck based on estimated unintentional lateral movement for the pass maneuver.

Abstract: Yaw rate estimating device includes: information acquirer that acquires information on front image and information on vehicle speed; lane recognizer that recognizes traveling lane drawn on traveling route of own vehicle and curvature thereof based on information on front image; direction change rate calculator that calculates change rate of direction of traveling lane based on information on curvature of traveling lane and vehicle speed; yaw angle change rate calculator that calculates change rate of yaw angle of own vehicle with respect to direction of traveling lane based on information on curvature of traveling lane and vehicle speed; and lane yaw rate estimator that estimates lane yaw rate based on change rate of direction of traveling lane and change rate of yaw angle of own vehicle with respect to direction of traveling lane, wherein estimated lane yaw rate is used as yaw rate of own vehicle.

Abstract: A parking collision avoidance system for a vehicle includes a sensing device configured to detect obstacles around the vehicle; and a control device that obtains type information of the obstacle and a point of expected collision timing with the obstacle according to sensing data received from the sensing device, determines a point of braking start timing of a braking device according to the point of the expected collision timing, and adjusts the point of the braking start timing according to the type information.

Abstract: Techniques for determining attributes associated with objects represented in temporal sensor data. In some examples, the techniques may include receiving sensor data including a representation of an object in an environment. The sensor data may be generated by a temporal sensor of a vehicle and, in some instances, a trajectory of the object or the vehicle may contribute to a distortion in the representation of the object. For instance, a shape of the representation of the object may be distorted relative to an actual shape of the object. The techniques may also include determining an attribute (e.g., velocity, bounding box, etc.) associated with the object based at least in part on a difference between the representation of the object and another representation of the object (e.g., in other sensor data) or the actual shape of the object.

Abstract: There is provided a vehicular illumination presentation system including: a first control system configured to control a vehicle interior illumination; a second control system configured to control a dimming unit located in a predetermined portion in a region surrounding a vehicle passenger compartment, the dimming unit being capable of adjusting a light transmittance; and a coordination control unit configured to coordinate an operation of the first control system and an operation of the second control system with each other. According to the vehicular illumination presentation system of the present disclosure, it is possible to form a comfortable private space and perform effective presentation without a need for an occupant to perform any special manual operation.

Abstract: Aspects of this technical solution can include determining, by one or more processors of a liquid collection system and based on respective amounts of liquid detected by a plurality of sensors and a velocity of a vehicle, a direction of movement of the liquid. The plurality of sensors can each be associated with respective ones of a plurality of receptacles. The plurality of sensors can be configured to detect respective amounts of liquid collected by respective openings of each of the plurality of receptacles associated with corresponding directions of movement of a liquid. The plurality of receptacles can be configured to collect at least a portion of the liquid via the respective openings.

Abstract: A waste management system audits waste collected by a service vehicle from clients. The system has a camera capturing images of waste collected in the collection hopper of the service vehicle. A controller compares the waste images to event criteria to determine if a service event has occurred and then associates a client with the service event, in which the client is identified by an accompanying identification system. The controller then identifies one or more waste images as event image data associated with the service event subsequent to determination that the service event has occurred and compares the event image data to content criteria to make an inference regarding a content of the collected waste. The inference is stored in association with the identified client and can trigger further action, for example notifications to the client or automated adjustments to invoicing to the client.

Abstract: After a driver parks a vehicle and has left the vehicle, a system relocates the autonomous vehicle into an optimized parking spot. The system obtains availability of other parking spots within a parking lot in which the vehicle is located. The system estimates whether any alternate parking spot would optimize cabin temperature and whether the energy consumed to complete an autonomous relocation of the vehicle will obtain a net savings in fuel economy relative to the energy expended by the relocation. The system determines the benefits of these optimized parking spots by using shaded and unshaded areas, GPS location of the vehicle, current date and time, and weather and fuel consumption estimates. If a favorable parking spot is determined, the autonomous vehicle relocates into the optimal alternate parking spot and informs the driver of the new location.

Abstract: In an embodiment an apparatus includes a path generator provided in a vehicle, wherein the path generator is configured to generate, based on a minimum turning radius of the vehicle, a default U-turn path and to generate a final U-turn path based on a path following control reference point of the vehicle which is based on the generated default U-turn path, and a controller configured to control autonomous driving of the vehicle to follow the generated final U-turn path.

Abstract: Techniques are described that facilitate predicting and minimizing risks associated with vehicle usage contexts. In one example, a method comprises obtaining, by a system comprising a processor, vehicle state information identifying occupants and objects of a vehicle and relative positions of the occupants and the objects about the vehicle in association with a current usage context of the vehicle. The method further comprises determining, by the system, an assessment of potential injuries associated with the current usage context of the vehicle based on analysis of the vehicle state information, wherein the analysis comprises evaluating potential movement of the occupants and the objects. The method further comprises determining, by the system, risk information regarding a risk associated with the current usage context of the vehicle as a function of the assessment.

Abstract: A system for operating an autonomous agent with incomplete environmental information can include and/or interface an autonomous operating system and an autonomous agent. A method for operating an autonomous agent with incomplete environmental information includes any or all of: receiving a set of inputs; determining a set of known objects in the ego vehicle's environment; determining a set of blind regions in the ego vehicle's environment; and inserting a set of virtual objects into the set of blind regions; selecting a set of virtual objects based on the set of blind regions; operating the autonomous agent based on the set of virtual objects; and/or any other suitable processes.

Abstract: A control unit of a server is a device that adjusts a parking position of a vehicle in a parking lot, and includes an acquisition unit that acquires the parking position of the vehicle scheduled to receive a package in the parking lot, and an adjustment information generation unit that generates adjustment information for adjusting parking of another vehicle in a parking slot adjacent to the parking position of the vehicle scheduled to receive the package in the parking lot such that a space is secured around the vehicle scheduled to receive the package.

Abstract: A method is disclosed for driving an emergency reaction system within a moving motor vehicle carrying at least one vehicle occupant. The method includes monitoring health conditions of the vehicle occupant. The method also includes determining whether the health conditions are below a critical threshold and, if so, continuing to monitor the health conditions of the vehicle occupant. If the health conditions exceed the critical threshold, an emergency alert is issued without waiting for the motor vehicle to stop, and an autonomous safe stop maneuver is performed if the motor vehicle is moving autonomously or includes an autonomous driving system and is allowed to operate automatically.

Abstract: A machine-learned architecture for estimating the cost determined by a cost function for a prediction node of a tree search for exploring potential paths for controlling a vehicle may include two portions: a set up portion that includes models trained to process static data and a second portion that processes dynamic object data. The respective portions of the architecture may comprise various models that determine intermediate outputs that may be projected into a space associated with estimated cost. That estimated cost may identify an estimate of an output of the cost function for paths that are based on a particular prediction node of the tree search.

Abstract: To provide a posture correction system, a posture correction method, and a program each adapted to correct a posture of a user. A posture correction system includes directing means for directing a line of sight of a user to a position higher than a position of a gazing region which the user gazes at, thereby prompting the user to stretch his/her cervical and thoracic vertebrae.

Abstract: Systems and methods are disclosed for generating vehicle insurance rates based on driver-independent variables and/or driver-dependent variables. Vehicle insurance rates may additionally or alternatively be based on changes in the level of autonomy of vehicles. In some embodiments, a density of vehicles near a target vehicle may be tracked. Vehicle insurance rates may be determined based on the vehicle density. Furthermore, systems and methods are disclosed for analyzing a driver's use of autonomous vehicle features and/or the driver's maintenance of the autonomous vehicle. The driver may also be taught certain driving skills by enabling vehicle teaching features. The driver's response to these teaching features may be monitored, and a reward or recommendation may be generated and provided to the driver based on the driver's response.

Abstract: Methods and apparatus for making autonomous vehicle handover decisions are described. A handover decision involves deciding if an autonomous vehicle should be handed off from one worker to another worker. The methods allow for decisions to be made in real or near real time shortly before an autonomous vehicle changes location. Worker time, if a handover is not implemented, is considered including the amount of worker time involved with the worker moving with the autonomous vehicle to the new location as compared to a new worker meeting the autonomous vehicle at the new location or on the way to the new location. Handover decisions can consider worker distribution and/or order priority. Such factors can be used to weight one or more time based cost values with a cost value representation of the cost if a handover is not implemented vs implementing a handover being compared to make the handover decision.

Abstract: Some aspects provide a method for instructing operation of a robotic floor-cleaning device based on the position of the robotic floor-cleaning device within a two-dimensional map of the workspace. A two-dimensional map of a workspace is generated using inputs from sensors positioned on a robotic floor-cleaning device to represent the multi-dimensional workspace of the robotic floor-cleaning device. The two-dimensional map is provided to a user on a user interface. A user may adjust the boundaries of the two-dimensional map through the user interface and select settings for map areas to control device operation in various areas of the workspace.

Abstract: System and techniques for vehicle operation safety model (VOSM) grade measurement are described herein. A data set of parameter measurements—defined by the VOSM—of multiple vehicles are obtained. A statistical value is then derived from a portion of the parameter measurements. A measurement from a subject vehicle is obtained that corresponds to the portion of the parameter measurements from which the statistical value was derived. The measurement is then compared to the statistical value to produce a safety grade for the subject vehicle.

Abstract: A method of operating an autonomous vehicle in a supervised autonomous mode is disclosed. A supervised autonomous mode can include the steps of receiving a vehicle data from a vehicle, presenting vehicle data at a remote station, receiving a supervisor input from a supervisor input device at the remote station, converting the supervisor input into a nudge for the motion planner of the vehicle associated with the received first set of vehicle data, wherein the nudge at least includes information on how to modify one or more elements of the cost function of the motion planner and transmitting the nudge from the remote station to the motion planner such that the nudge at least temporarily updates a cost function based model of the motion planner based on the nudge.

Abstract: According to one aspect, systems and techniques for adaptive trust calibration may include usage of a driving style predictor, including a memory and a processor. The memory may store one or more instructions and the processor may execute one or more of the instructions stored on the memory to perform one or more acts, actions, or steps, such as receiving a current automated vehicle (AV) driving style, receiving an indication of an event and an associated event type, receiving an indication of a driver takeover, concatenating the current AV driving style and one or more of the event type or the driver takeover to generate an input, and passing the input through a neural network, which may include a gated recurrent unit (GRU), to generate a preference change associated with the AV driving style.

Abstract: Provided is a robot for transporting patient treatment tools. The robot includes a main body providing a space open in a front side of the main body and capable of traveling on the ground; a communication unit installed in the main body and wirelessly connected to the call signal generator; a control unit located on an upper side of the main body and manipulated by a user; an elevating structure slidably installed in the space of the main body; elevating means for elevating the elevating structure; a storage box supported by the elevating structure, temporarily accommodating treatment tools introduced from the outside, being movable forwards and backwards, and moving forwards and opened to send the treatment tools to the outside; and a storage box driving unit for moving the storage box forwards and backwards.

Abstract: A first driving solution for a vehicle along a portion of a route is determined based on an agent detected in the vehicle's environment following a first trajectory of a plurality of possible trajectories. A switching time is determined for the vehicle to deviate from the first driving solution for a situation in which the agent is following a second trajectory of the plurality of possible trajectories. The first driving solution is revised such that the vehicle will be able to switch from the revised first driving solution to another driving solution at the switching time in case if the detected agent is following the second trajectory.

Abstract: The present invention relates to the field of intelligent vehicles, and more specifically, to a human-machine shared control method based on trajectory prediction. It comprises: establishing a road-vehicle model based on vehicle-related parameters and then designing a path-tracking controller; further predicting the driver's driving trajectory, evaluating the driving risk, and switching the control power between the automatic system and the human driver based on the driving risk. The present invention ensures that when the driver's inputs will cause high risk to the vehicle, the driver's input is deprived of; and that when the driver's driving inputs will not cause high risk to the vehicle, the driving is carried out by the driver, so that in the case where the automatic system is having a problem, the driver can effectively realize a safe intervention, and the safety of the intelligent driving is improved.

Abstract: A warehouse management system is provided for controlling a picking operation with at least one order picking trolley for storing items of a set of picking orders, at least one storage unit with storage areas for storing the items, and with at least one access station for accessing the items by an order picker. The order picking trolley and the access station are each provided with an eye-catching transmitter and at least one of the eye-catching transmitters has a display area (37, 55) with a remotely switchable color. The warehouse management system is configured to automatically switch the color of the at least one remotely switchable eye-catching transmitter to the color of the other eye-catching transmitter when it has been detected that the item is positioned ready for access.

Abstract: A method includes: detecting a transporter allocation trigger associated with a mobile computing device disposed in a facility; in response to detecting the transporter allocation trigger, selecting a transporter identifier of an autonomous transporter disposed in the facility; selecting a joint notification parameter; causing the mobile computing device to generate a notification according to the joint notification parameter; and transmitting the joint notification parameter to the autonomous transporter, to cause the autonomous transporter to generate a visual notification corresponding to the notification.

Abstract: An automated driving mode of a vehicle is automatically terminated if, due to a manual steering torque acting on the steering wheel of the vehicle, a system steering torque generated by a control system of an assistance system for automated driving mode in terms of amount is exceeded by a predetermined first value if at least one hand of a vehicle user is detected on the steering wheel of the vehicle, is exceeded by a predetermined second value if neither of the vehicle user's hands is detected on the steering wheel, or is exceeded by a predetermined third value if it is determined that the vehicle user is distracted from the driving situation, or if it is determined that there is a lateral collision risk for the vehicle and the manual steering torque of the vehicle user is acting in the direction of the collision risk.

Abstract: A computer implemented method for evaluating autonomous vehicle safety that includes defining criteria for safety of autonomous vehicles in a test space, and dividing the test space into an intended test space and a un-intended test space for the criteria for safety of autonomous vehicles. The intended test space includes characterizations for the autonomous vehicle that can be quantified, and the un-intended test space includes characterizations that are not quantifiable. The method further includes measuring the safety of the autonomous vehicles in the intended test space. The applying the un-intended test space is applied to the intended test space as feedback into the intended test space; and evaluating the intended test space including the feedback from the unintended test space using a combined simulation of peripheral vehicles and autonomous vehicles to provide the evaluation of autonomous vehicle safety.

Abstract: An electronic control device apparatus includes a storage apparatus, a communication apparatus, and a processing apparatus. The processing apparatus determines, based on the level of the shape data included in external map information acquired by the communication apparatus, one of the plurality of control modes with different control methods of the vehicle as the control mode of the autonomous driving control.

Abstract: A reinforcement learning-based sensor data management system includes a processor configured to: manage virtualized objects that correspond to sensors included in a sensor network to update data received from each sensor and queries representing a data quality requested by an application; calculate an abstracted action that abstracts a size of an action space of the sensor network based on present state information of the virtualized objects and the queries; calculate scores for virtualized objects based on position relationships between the calculated abstracted action the virtualized objects; and assign priorities to the virtualized objects based on the calculated scores to update data received from the sensors to the virtualized objects according to the priorities.

Abstract: In embodiments of an autonomous vehicle platform and safety architecture, safety managers of a safety-critical system monitor outputs of linked components of the safety-critical system. The linked components comprise at least three components, each of which is configured to produce output indicative of a same event independent from the other linked components by using different input information than the other linked components. The safety managers also compare the outputs of the linked components to determine whether each output indicates the occurrence of a same event. When the output of one linked component does not indicate the occurrence of an event that is indicated by the outputs of the other linked components, the safety managers identify the one linked component as having failed. Based on this, the outputs of the other linked components are used to carry out operations of the safety-critical system without using the output of the failed component.

Abstract: The present disclosure provides methods and techniques for evaluating and improving algorithms for autonomous driving planning and control (PNC), using one or more metrics (e.g., similarity scores) computed based on expert demonstrations. For example, the one or more metrics allow for improving PNC based on human, as opposed to or in addition to optimizing certain oversimplified properties, such as the least distance or time, as an objective. When driving in certain scenarios, such as taking a turn, people may drive in a distributed probability pattern instead of in a uniform line (e.g., different speeds and different curvatures at the same corner). As such, there can be more than one “correct” control trajectory for an autonomous vehicle to perform in the same turn. Safety, comfort, speeds, and other criteria may lead to different preferences and judgment as to how well the controlled trajectory has been computed.

Abstract: The subject matter described in this specification is directed to a system and techniques for operating an autonomous vehicle (AV) at a multi-way stop intersection. After detecting the AV is at a primary stopline of the multi-way stop intersection, a planned travel path though the multi-way stop intersection is obtained. If the planned travel path of the AV through the multi-way stop intersection satisfies a set of one or more clearance criteria, the AV proceeds past the primary stopline. The clearance criteria include a criterion that is satisfied in response to detecting the AV is clear to safely merge into a travel lane corresponding to the planned travel path.

Abstract: The disclosure includes embodiments for a medic system to respond to a medical condition of a vehicle occupant. A method according to some embodiments is executed by a processor. The method also includes determining, by the processor, that a driver of an ego vehicle is experiencing a debilitating medical condition. The method also includes overriding a protocol to decrease an autonomy level of the ego vehicle responsive to inattentiveness of the driver to a driving interface of the ego vehicle so that the driver can be inattentive to the driving interface and the autonomy level is not decreased. The method also includes modifying an operation of an autonomous driving system of the ego vehicle to increase the autonomy level of the ego vehicle to decrease a driving responsibility of the driver responsive to the debilitating medical condition.

Abstract: In one embodiment, a method includes determining a plurality of available locations for a vehicle to pick up or drop off a user in an area based on sensor data that is captured by the vehicle and is associated with physical characteristics of the area. The method includes calculating a viability value for each of the plurality of available locations. The viability value is calculated based on the physical characteristics of the area as determined from the sensor data. The method includes ranking the plurality of available locations according to the viability values of the plurality of available locations. An available location with a higher viability value is ranked above an available location with a lower viability value. The method includes sending instructions to present, on a computing device, one or more selectable locations of the plurality of available locations based on the ranking.

Abstract: An automated vehicle assistance system is provided for supervised or unsupervised vehicle movement. The system includes a control system and a first sensor system. The first sensor system may receive first image data of a scene and may output a first disparity map and a first confidence map based on the first image data. The control system may output a video stream based on the first disparity map and the first confidence map. The vehicle assistance system also may include a second sensor system that receives second image data of at least a portion of the scene that outputs a second confidence map based on second image data. The video stream may include super-frames, with each super-frame including a 2D image of the scene, a depth map corresponding to the 2D image, and a certainty map corresponding to the depth map.

Abstract: A mobile robot of the present disclosure includes: a traveling unit configured to move a main body; a lidar sensor configured to acquire terrain information outside the main body; a camera sensor configured to acquire an image outside the main body; and a controller configured to fuse the image and a detection signal of the lidar sensor to select a front edge for the next movement and set a target location of the next movement at the front edge to perform mapping travelling. Therefore, in a situation where there is no map, the mobile robot can provide an accurate map with a minimum speed change when travelling while drawing the map.

Abstract: A vehicle includes a storage device configured to store an estimation algorithm configured to output a degree of deterioration of a component mounted on the vehicle in response to an input of a value of a parameter related to the component, a sensor configured to detect the value of the parameter, and a control device. The control device is configured to execute a performance test by autonomous driving of the vehicle, acquire data indicating performance of the component during the performance test, and update the estimation algorithm by using the data acquired during the performance test.

Abstract: The disclosure relates to a lane departure warning method and a lane departure warning system. The lane departure warning method of the disclosure includes: a warning area calculation step in which a warning area for lane departure of a vehicle is calculated based on information about the vehicle and information around the vehicle; a decision making step in which a current position of the vehicle is compared with the warning area calculated in the warning area calculation step, to determine whether the vehicle is located in the warning area and output a decision instruction; and a warning step in which a warning action is performed based on the decision instruction. According to the disclosure, a lane departure status of the vehicle can be more accurately estimated and timely warning can be performed when there is a tendency for lane departure.

Abstract: A manager installed in a vehicle includes: a first accepting unit that accepts a plurality of kinematic plans from a plurality of ADAS applications; an arbitration unit that arbitrates the kinematic plans; a calculation unit that calculates a motion request based on an arbitration result by the arbitration unit; and a distribution unit that distributes the motion request to at least one actuator system, wherein the first accepting unit accepts information relating to the actuator system to which the distribution unit distributes the motion request from the ADAS applications, along with the kinematic plans.

Abstract: Methods, systems, and programs are presented for detecting impaired views in monitoring cameras. One method includes training a rotation classifier with unsupervised learning utilizing a first set of images. The rotation classifier is configured to receive an input image and generate a rotation feature embedding for the input image. In addition, the method includes training an impairment classifier with supervised learning utilizing a second set of images, impairment labels for each of the second set of images, and the rotation feature embedding, generated by the rotation classifier, for each of the second set of images. The method further includes accessing a vehicle image captured by a camera on a vehicle, and providing the vehicle image to the impairment classifier as input, and the impairment classifier outputs a camera impairment from a set of camera impairment categories. Further, the vehicle image and the camera impairment are presented on a user interface.

Abstract: Techniques for determining a safety area for a vehicle are discussed herein. In some cases, a first safety area can be based on a vehicle travelling through an environment and a second safety area can be based on a steering control or a velocity of the vehicle. A width of the safety areas can be updated based on a position of a bounding box associated with the vehicle. The position can be based on the vehicle traversing along a trajectory. Sensor data can be filtered based on the sensor data falling within the safety area(s).

Abstract: Described herein relates to a system and method for system of and method for optimizing real-time workplace safety monitoring by facilitating hazard avoidance within an industrial environment. In an embodiment, the global access protection (hereinafter “GAP”) system may comprise a computing device comprising at least one processor, such that the computing device may be communicatively coupled to at least one Global Positioning System (hereinafter “GPS”) system. Additionally, in this embodiment, the computing device may be integrated within the at least one beacon and/or the at least one receiver. In this manner, the at least one beacon and/or at least one receiver may be configured to output and/or input a GPS, RTK GPS, and/or any positioning system known in the art, such that the GAP system may be configured to determine a distance between the at least one beacon and the at least one receiver within the industrial environment.