Abstract: A servomotor control device includes a servomotor, driven body, connection mechanism, first position detection section, second position detection section, and motor control unit. The motor control unit has: a dual position control section that performs semi-closed FB control based on a high-frequency component of a first deviation between a position command value and the position of the servomotor detected by the first position detection section, and full-closed FB control based on a low-frequency component of a second deviation between the position command value and the position of the driven body detected by the second position detection section; an acquisition section that acquires a magnitude of rigidity of the connection mechanism; and a varying section that varies a proportion of the semi-closed FB control to full-closed FB control in the dual position control section, in response to the acquired magnitude of rigidity of the connection mechanism.

Abstract: A manufacturing device monitoring system includes a plurality of manufacturing devices and a remote monitoring device. The manufacturing device includes a work unit, an equipment notifier, an error detector, and an error notifier. The error notifier determines whether or not an error detected by the error detector may be corrected by an operation from the remote monitoring device, notifies the remote monitoring device of the occurrence of the error in a case where the error can be corrected, and operates the equipment notifier to notify a first notification pattern in a case where the error cannot be corrected.

Abstract: Method, and corresponding system, for receiving and adaptively compressing sensor data for an operating manufacturing machine. The method includes determining the sensor data values at the working tool positions based on a time correlation of the values of the sensor data relative to time and the working tool positions relative to time. Tool control magnitude values relative to the working tool positions are determined based on the process data. The method further includes determining a magnitude differential, relative to the working tool positions, between the sensor data values and the tool control magnitude values. Scoring data is determined by applying a scoring function to the magnitude differential. The magnitude differential data is compressed based at least in part on the scoring data. The method further includes decompressing the magnitude differential data and determining the sensor data values versus the working tool positions based on the magnitude differential data.

Abstract: An agent engine allocates a collection of agents to scan the surface of an object model. Each agent operates autonomously and implements particular behaviors based on the actions of nearby agents. Accordingly, the collection of agents exhibits swarm-like behavior. Over a sequence of time steps, the agents traverse the surface of the object model. Each agent acts to avoid other agents, thereby maintaining a relatively consistent distribution of agents across the surface of the object model over all time steps. At a given time step, the agent engine generates a slice through the object model that intersects each agent in a group of agents. The slice associated with a given time step represents a set of locations where material should be deposited to fabricate a 3D object. Based on a set of such slices, a robot engine causes a robot to fabricate the 3D object.

Abstract: A method includes accessing a first model defining a shape of a part. The shape of the part is segregated into a plurality of predefined shapes selected from a library of predefined shapes. The predefined models for each of plurality of predefined shapes are assembled into a second model defining the shape of the part. The part is additively manufactured according to the second model.

Abstract: Disclosed herein are an apparatus and method for verifying and correcting degree of 3D-printed joints movement. A method for correcting a print position of a three-dimensional (3D) object is performed by a 3D object print position correction apparatus, and includes setting at least one adjacent mesh of a 3D object in which multiple shells are connected to each other through a joint structure, calculating movement degree information for the joint structure of the 3D object using the set adjacent mesh, and correcting a print position of the 3D object such that the print position matches the calculated movement degree information.

Abstract: A system for manufacturing a discrete object from an additively manufactured body of material including a precursor to a discrete object and at least a reference feature is disclosed. The system includes an automated manufacturing device, the automated manufacturing device including at least a controller configured to receive a graphical representation of precursor to a discrete object, receive a graphical representation of at least a reference feature on the precursor to the discrete object, and generate a computer model of the body of material, wherein the computer model of the body of material includes the graphical representation of the precursor to the discrete object and the graphical representation of the at least a reference feature.

Abstract: Mold lock is remediated by performing a layer-by-layer, two-dimensional analysis to identify unconstrained removal paths for any support structure or material within each two-dimensional layer, and then ensuring that aligned draw paths are present for all adjacent layers, all as more specifically described herein. Where locking conditions are identified, a sequence of modification rules are then applied, such as by breaking support structures into multiple, independently removable pieces. By addressing mold lock as a series of interrelated two-dimensional geometric problems, and reserving three-dimensional remediation strategies for more challenging, complex mold lock conditions, substantial advantages can accrue in terms of computational speed and efficiency.

Abstract: A system includes a processor configured to determine that a first user will transition from a first climate-controllable environment to a second climate-controllable environment within a threshold time. The processor is also configured to compare first and second environment temperatures. The processor is further configured to detect whether a second-user control device is in communication with a second-environment climate control and set the second-environment climate control to a desired temperature, based on the first environment temperature, responsive to an absence of the second-user control device.

Abstract: A manufacturing line includes a receiving unit that receives sensor data indicative of a measured value by a sensor provided near a manufacturing device constituting a manufacturing line, a sensor determining unit that determines whether the measured value indicated by the sensor data exceeds a first sensor threshold value indicative of a predetermined range, and a notifying unit that sends a sensor abnormality notification, which notifies a user of the client terminal that the manufacturing device malfunctions, in a case where the sensor determining unit determines that the measured value exceeds the first sensor threshold value.

Abstract: Disclosed herein is a worksite automation process that involves: generating a first sequence of tasks to build the product according to a model. The process further involves causing one or more robotic devices to build the product by beginning to execute the first sequence of tasks. Further, during the execution of the first sequence of tasks, performing a buildability analysis to determine a feasibility of completing the product by executing the first sequence of tasks. Based on the analysis, determining that it is not feasible to complete the product by executing the first sequence of tasks, and in response, generating a second sequence of tasks to complete the product according to the model. Then, causing the one or more robotic devices to continue building the product by beginning to execute the second sequence of tasks.

Abstract: Embodiments presented herein provide techniques for planning and scheduling in a factory. The technique begins by generating a bottleneck loading plan from a plurality of inputs. A simulation is run using the bottleneck loading plan. The factory is simulated using decisions made based on the bottleneck loading plan and a lot-to-machine schedule is generated with the simulation bottleneck loading plan.

Abstract: A robot learning system for trajectory learning of a robot (RB) having a robot arm between a base and a tool center point (TCP). A user interface allows the user to control the robot arm in order to follow a desired trajectory during a real-time. A probe sensor (PS) is mounted on the TCP during the learning session. The probe sensor (PS) measures a distance parameter (Z) indicative of distance from the TCP and a surface forming the trajectory to be followed, and an orientation parameter (X, Y) indicative of orientation of the TCP and the surface forming the trajectory to be followed. These distance and orientation data are provided as a feedback to the controller of the robot (CTL) during the real-time learning session, thereby allowing the robot controller software to assist the user in following a desired trajectory in a continuous manner.

Abstract: A method for remote monitoring of an industrial machine having a relay based or PLC based controller includes steps of providing a hardware interface module for directly interfacing with the relay based or PLC based controller of the industrial machine, directly interfacing the hardware interface module with the relay based or PLC based controller to identify occurrence of power cycles of the industrial machine, registering the hardware interface module through a portal accessible through a network, communicating the occurrence of the power cycles of the industrial machine detected with the hardware interface module to a database in operative communication with the portal and storing the occurrence of the power cycles within the database, and providing a user interface indicative of performance of the industrial machine based on the power cycles of the industrial machine detected with the hardware interface module and stored in the database.

Abstract: A method, apparatus, and system are for determining signal rules and annotating data. The method, according to an embodiment, includes: determining data obtaining logic based on assembly model information corresponding to the assembly; wherein the data obtaining logic includes a to-be-obtained data object and an obtaining rule; determining at least one physical signal corresponding to the data obtaining logic; and determining, based on the data obtaining logic and the at least one physical signal corresponding to the data obtaining logic, a signal rule corresponding to the obtaining rule. By annotating the running data of an assembly, the context of the data may be indicated, so that the running data of the assembly can be made more consistent, easier to maintain, and/or applied to a new environment. Moreover, since the annotation information of data can adopt a common format, it may be more suitable for information migration and system configuration.

Abstract: A system and method for unsupervised root cause analysis of machine failures. The method includes analyzing, via at least unsupervised machine learning, a plurality of sensory inputs that are proximate to a machine failure, wherein the output of the unsupervised machine learning includes at least one anomaly; identifying, based on the output at least one anomaly, at least one pattern; generating, based on the at least one pattern and the proximate sensory inputs, an attribution dataset, the attribution dataset including a plurality of the proximate sensory inputs leading to the machine failure; and generating, based on the attribution dataset, at least one analytic, wherein the at least one analytic includes at least one root cause anomaly representing a root cause of the machine failure.

Abstract: Methods, apparatus, systems and articles of manufacture (e.g., physical storage media) to manage deployed drones are disclosed. Example methods disclosed herein include detecting, by a first drone, whether the first drone is in communication with a command center via a first communication network to determine a configuration parameter of a first message to broadcast discovery information associated with the first drone. Disclosed example methods also include, in response to the first drone being in communication with the command center via the first communication network, broadcasting, from the first drone, the first message configured with a first value for the configuration parameter. Disclosed example methods further include, in response to the first drone not being in communication with the command center via the first communication network, broadcasting, from the first drone, the first message configured with a second value for the configuration parameter different from the first value.

Abstract: Methods and systems are disclosed for determining a vehicle view based on a relative location of a remote display. An example vehicle includes a plurality of cameras configured to capture images of the vehicle surroundings. The vehicle also includes a communication system, and a processor. The processor is configured to stitch together images captured by the plurality of cameras, determine a relative location of a remote display with respect to the vehicle, determine a vehicle view based on the determined relative location, and transmit the vehicle view to the remote display.

Abstract: Unmanned ground vehicle teleoperation is provided. A forward looking scene understanding system is employed. Region of interest based compression is employed. Driving specific scene virtualization is employed. Link quality measurement is employed. A hared control autonomy system is used.

Abstract: A system for autonomous driving of a vehicle having a steering system and a braking system is disclosed. The system comprises a sensor capable of gathering data relating to a driving environment, a control system programmed to control the steering system and the braking system to drive the vehicle without unrequested user intervention, in response to data gathered by the sensor, a user output device capable of presenting human readable text or speech to a user when an aspect of the driving environment detected by the sensor renders the control system unable to determine a next driving action; and, a user input device coupled to the control system. The user input device is capable of receiving user input to instruct the control system to take a user-preferred driving action. The control system is capable of instructing the steering system and the braking system to execute the user-preferred driving action.

Abstract: A processing apparatus comprises a first determination unit configured to determine, based on peripheral information of a self-vehicle, whether another vehicle that is stopped exists on one side of a road in a width direction; a second determination unit configured to determine, based on the peripheral information, whether a walker exists on the other side of the road in the width direction; and a setting unit configured to, if the other vehicle exists on the one side of the road in the width direction, and the walker exists on the other side of the road in the width direction, set, for the other vehicle, a second warning region wider than a first warning region in a case in which the other vehicle exists, and the walker does not exist.

Abstract: A flood level detection system for a vehicle, which includes at least one sensor, and an interface. The sensor detects the depth of an area of accumulated water in proximity to the vehicle, and then communicates the depth of the area of accumulated water to the interface. The interface then communicates to the driver of the vehicle whether the depth of the area of accumulated water is greater than or less than the maximum allowable depth that the vehicle may tolerate. The vehicle may include a driver Human-Machine Interface (HMI), and the interface may be part of the driver HMI. However, in other embodiments, the interface may be part of the vehicle instrument cluster, or other part of the vehicle. The sensor in one embodiment is a laser sensor, but in other embodiments, the sensor may be a LIDAR sensor, a LADAR sensor, radar, or a sonar sensor.

Abstract: A vehicle system controller having an asymmetric system architecture and a method of operating the vehicle system controller is provided. The vehicle system controller includes a primary controller and a secondary controller in communications with the vehicle systems. Each of the controllers include a memory unit containing software application and a processor for executing the software to generate commands for the vehicle systems. The memory unit of the secondary controller contains only a subset of the total software applications contained in the memory unit of the primary controller. The subset of software applications is only for the operation of pre-identified features of the vehicle systems. The vehicle systems are configured to default to commands from the primary controller, but switches to the commands from the secondary controller for a predetermined length of time if the primary controller becomes fail-silent.

Abstract: An information processing method includes: acquiring, from one or more first vehicles, manual driving information for each of the first vehicles; acquiring, from one or more second vehicles, automatic driving information for each of the second vehicles; calculating, for each area, a first value of a driving parameter correlated with a degree of difficulty in driving according to the manual driving information; calculating, for the each area, a second value of the driving parameter according to the automatic driving information; comparing the first value with the second value for the each area to determine at least one difficult area in which travel of a vehicle by automatic driving is difficult; and creating difficult area information.

Abstract: A vehicle control system includes a display unit configured to display an image, a vehicle control unit configured to perform a driving support by different degrees, and a display control unit configured to display an image indicating an action requested for an occupant at a display position corresponding to an image related to the degree of the driving support on the display unit.

Abstract: A vehicle control system includes a driving support control unit configured to execute a driving support, an information output unit configured to output information, an operation unit configured to receive an operation by an occupant of a vehicle, and an information output control unit configured to cause the information output unit to output information indicating that a start of the driving support by the driving support control unit is possible in a case where the operation by the operation unit is received.

Abstract: A vehicle control system includes a first detection unit configured to detect an operation of a driving operation element by an occupant, a second detection unit configured to detect a direction of a face or a line of sight of the occupant, and a switching control unit configured to switch an automatic driving mode executed by an automatic driving control unit to one of a plurality of automatic driving modes including a first automatic driving mode and a second automatic driving mode.

Abstract: An ambulatory medical device that can communicate with a vehicle is described. An example of the ambulatory medical device includes one or more sensing electrodes configured to sense cardiopulmonary signals of a patient, a network interface, and one or more processors configured to receive signals from one or more vehicle occupancy sensors, detect usage of the ambulatory medical device in a vehicle based on the received signals from the one or more vehicle occupancy sensors, detect at least one of a medical event and a medical premonitory event of the patient based on the sensed cardiopulmonary signals, and provide driving control information to the vehicle, via the network interface, based at least in part on the detected usage of the ambulatory medical device in the vehicle and the detected medical event or medical premonitory event of the patient.

Abstract: A system for tracking and reporting changes to a parcel of land comprising one or more stationary or mobile sensors mounted to fixed positions and/or unmanned vehicles, and sophisticated distributed network software for controlling the sensors and vehicles, analyzing the sensor data, and storing the data. The network software controls the sensor data gathering, the route any vehicles travel, and all the timing for data gathering. If unmanned vehicles are used, the routes and starting times can factor in weather, people and vehicle traffic, air traffic control information, and the previously data obtained sensor data from vehicle sensors on previous trips. Fixed sensors are environmentally protected and connected via wireless or wired signals. Vehicles can be stored in environmentally protective enclosures which can recharge or refuel the vehicles, and/or download any sensor data they obtained on previous surveys.

Abstract: In one embodiment, a computer system generates a first vehicular path based on map information. The system collects data points representing geographical coordinates of vehicles that drove on a vehicular path lane at different points in time. The system segments the first vehicular path into path segments based on the collected data points. For each of the path segments, the system applies a smoothing function to select a subset of the data points that are within a predetermined proximity of the corresponding path segment and calculates a segment reference point to represent the path segment by combining the selected data points. The segment reference points of the path segments of the first vehicular path are interpolated to generate a second vehicular path such that the second vehicular path is used as a reference line to control ADVs driving on the first vehicular path.

Abstract: A map-localization system for navigating an automated vehicle includes a path-detector, a digital-map, and a controller. The path-detector is used to detect observed-geometries of a roadway traveled by a host-vehicle. The digital-map indicates mapped-geometries of roadways available for travel by the host-vehicle. The controller is in communication with the path-detector and the digital-map. The controller is configured to determine a location of the host-vehicle on the digital-map based on a comparison of the observed-geometries to the mapped-geometries.

Abstract: Described is a system (and method) for providing a flexible decision system for autonomous driving. The system may include a framework that allows a decision system to switch between a deliberate rule-based decision framework and an intuitive machine-learning model-based decision framework. The system may invoke the appropriate framework (or subsystem) based on a particular set of driving conditions or environment. Accordingly, the system described herein may provide an efficient and adaptable decision system for autonomous driving.

Abstract: System and method for controlling an aerial system to perform a selected operation using an easy-to-use release and auto-positioning process.

Abstract: The present invention relates to unmanned aerial vehicles, and specifically discloses a method and a system for controlling an aircraft to automatically return and an unmanned aerial vehicle. The method includes: when the magnetometer is invalid or encounters strong magnetic interference, assuming that a track angle is equivalent to the head direction, and accelerating the aircraft in a head direction; determining whether a speed obtained after the aircraft is accelerated reaches a preset value; if the speed reaches the preset value, obtaining the track angle of the aircraft according to the speed; obtaining a current location and a home point of the aircraft by using a positioning system that can provide global or local coordinates, to obtain a heading angle of the aircraft; determining whether a difference between the heading angle of the aircraft and the track angle of the aircraft is less than a fixed value; and if the difference is less than the fixed value, controlling the aircraft to directly return.

Abstract: A system and method for mission planning and flight automation for an unmanned aircraft comprising generating an aerial imagery map of a capture area; generating a flight plan based on criteria for capturing images used to create a model of a feature present in the images; comparing the generated aerial imagery map with the generated flight plan; determining whether there is a possible collision between an obstacle associated with the generated aerial imagery map and the unmanned aircraft along a flight path of the generated flight plan; and executing, based on the determination, the generated flight plan.

Abstract: Systems and methods are provided for controlling a vehicle. In one embodiment, a method includes receiving vehicle state data, high-definition map data, and vehicle object environment data, generating a trajectory path that is optimal with respect to the received data, determining whether to update the trajectory path using Bézier curves based on the received data, performing an assessment of the trajectory using properties of Bézier curves, and generating an updated trajectory.

Abstract: An object-detection system suitable for use on an autonomous vehicle includes a camera, a radar-sensor, and a controller. The camera detects a travel-lane of a roadway traveled by a host-vehicle. The radar-sensor detects targets in a field-of-view of the radar-sensor. The field-of-view includes the roadway, wherein the roadway defines a boundary of the roadway detected by the radar-sensor. The controller is in communication with the camera and the radar-sensor. The controller determines that a collection of targets is a stationary-object that defines a line. The controller classifies the stationary-object as an overpass when the line extends beyond the boundary of the roadway. The controller classifies the stationary-object as an impediment when the line overlays a portion of the travel-lane traveled by the host-vehicle and does not extend beyond the boundary of the roadway.

Abstract: An automatic driving system includes an electronic control unit. The electronic control unit is configured to create a traveling plan including a control target value of automatic driving control of a vehicle based on a position of the vehicle of a map, a vehicle state, and an external environment, to calculate an abnormality value, to determine, based on the abnormality value, whether the vehicle is an a normal state, an abnormal state, or an intermediate state, and to create an abnormal traveling plan as the traveling plan when it has been determined that the vehicle is in the abnormal state.

Abstract: A running track determining device capable of appropriately determining a running track of a subject vehicle in the future in a speedy manner and an automatic driving apparatus including the running track determining device is provided. A running track determining device (1) includes an ECU (2). The ECU (2) calculates a risk potential (Prisk) representing an area having a possibility of the presence of a traffic participant from the present to the future in surroundings of the subject vehicle (3) in accordance with surrounding status data (D_info) detected by a status detecting device (4), calculates a benefit potential (Pbnf) representing an ideal running area in the future in which the subject vehicle (3) should run, and determines a running track (Tr_sk) of the subject vehicle (3) in the future by using the risk potential (Prisk) and the benefit potential (Pbnf).

Abstract: Systems and method are provided for controlling a vehicle. In one embodiment, a method includes: monitoring a health of the vehicle; generating a first driving plan; generating a second driving plan configured to bring the vehicle to a stop at a predetermined rate; commanding the vehicle to execute the first driving plan in response to the health of the vehicle staying above a predetermined health threshold; and commanding the vehicle to execute the second driving plan in response to the health of the vehicle falling below the predetermined health threshold.

Abstract: A system to reduce vehicle resource depletion risk which includes a memory, controller, efficiency module, mobile computing device, and fleet vehicle. The memory includes executable instructions. The controller executes the instructions. The controller communicates with an efficiency module. The efficiency module causes a fleet vehicle to optimally perform a rideshare task. The mobile computing device generates first location data and communicates the first location data to the controller. The fleet vehicle includes a vehicle system and a vehicle controls device and can communicate with the controller. The vehicle system generates second location data. The vehicle controls device commands the fleet vehicle to perform a rideshare task.

Abstract: A method for autonomous operation of a compression apparatus for compressing a ground, the method comprising the steps: choosing a surface to be processed of the ground; preparing the compression apparatus or at least a portion of the surface to be processed so that the compression apparatus automatically processes the surface to be processed in an autonomous operation so that substantially each spot of the surface to be processed is processed at least once; moving a position-determination device along a path which represents at least a portion of an outer boundary of the surface to be processed and capturing position data by the position determination device at least in an intermittent manner while moving the position determination device along the path; generating electronic information regarding a position of the outer boundary of the surface to be processed based on captured position data of the path.

Abstract: A path of travel used by an autopilot operation system for auto-guidance of a mobile machine is defined, transparently to a human operator, in response to the human operator engaging and disengaging operation of an implement coupled with the mobile machine. The auto-guidance of the mobile machine is activated, transparently to the human operator, in response to the human operator engaging the implement a second time.

Abstract: State of an autonomous driving vehicle (ADV) is measured and stored for a location and speed of the ADV. Later, the state of the ADV is measured for the location and speed corresponding to a previously stored state of the ADV at the same location and speed. Fields of the measured stored states of the ADV are compared. If one or more differences between the measured and stored ADV states exceeds a threshold, then one or more control input parameters of the ADV is adjusted, such as steering, braking, or throttle. Differences may be attributable to road conditions or to state of servicing of the ADV. Differences between measured and stored states of the ADV can be passed to a service module. Service module can access crowd sourced data to determine whether one or more control input parameters for a driving state of one or more ADVs should be updated.

Abstract: In a vehicle control device, a control unit acquires a passing target point representing a position of a point that an own vehicle aims to pass in the future (S140) and generates a trajectory for passing the passing target point (S150). Then, the control unit calculates and outputs a control amount of the own vehicle for causing the own vehicle to travel according to the trajectory (S170).

Abstract: When a transmission condition regarding a state detected by a state detection unit (vehicle sensor, operation detection sensor, external environment sensor, or internal environment sensor) is satisfied while a travel controller performs a travel control, a vehicle control system transmits attentional state information representing a travel state, an operation state, or an environment state to a travel assist server through a communication device.

Abstract: A track in a transport system includes a standby section associated with a certain processing apparatus to allow a transport vehicle to wait. When determining a transport request to transport a FOUP to a load port of the certain processing apparatus exists, the controller allocates, to the transport vehicle, a first transport command to transport the FOUP to the standby section. When reaching the standby section, the transport vehicle waits while holding the FOUP. Subsequently, when determining that the FOUP is transportable to the load port of the certain processing apparatus, the controller allocates, to the transport vehicle, a second transport command to transport the FOUP to the load port of the certain processing apparatus.

Abstract: A vehicle control system includes a recognition unit that recognizes lane markers on a road; and a steering control unit that performs first steering control so that a subject vehicle does not deviate from a traveling lane on which the subject vehicle travels on the basis of a lane marker demarcating the traveling lane among the lane markers recognized by the recognition unit, and when a lane marker demarcating the traveling lane is not recognized by the recognition unit in front of the subject vehicle or when an index value indicating a degree of recognition of the lane marker is smaller than a threshold value, the steering control unit limits the first steering control, determines a target steering angle in a range of predetermined angles with reference to a steering angle at the time of traveling in a straight line of the subject vehicle, and performs second steering control at the determined target steering angle.

Abstract: The present teaching relates to a method, system, medium, and implementation of processing image data in an autonomous driving vehicle. Sensor data acquired by one or more types of sensors deployed on the vehicle are continuously received. The sensor data provide different information about surrounding of the vehicle. Based on a first data set acquired by a first sensor of a first type of the one or more types of sensors at a specific time, an object is detected, where the first data set provides a first type of information about the surrounding of the vehicle. Depth information of the object is then estimated via object centric stereo at object level based on the object detected as well as a second data set acquired by a second sensor of the first type of the one or more types of sensors at the specific time. The second data set provides the first type of information about the surrounding of the vehicle with a different perspective as compared with the first data set.

Abstract: The present teaching relates to a method, system, medium, and implementation of processing image data in an autonomous driving vehicle. Sensor data acquired by one or more types of sensors deployed on the vehicle are continuously received to provide different types of information about surrounding of the vehicle. Based on a first data set acquired by a first sensor of a first type of sensors at a specific time, an object is detected, where the first data set provides a first type of information with a first perspective. Depth information of the object is estimated via object centric stereo based on the object and a second data set, acquired at the specific time by a second sensor of the first type of sensors with a second perspective. The estimated depth information is further enhanced based on a third data set acquired by a third sensor of a second type of sensors at the specific time, providing a second type of information about the surrounding of the vehicle.