Abstract: Techniques for validating operation of vehicle safety system components are discussed herein. Vehicle log data processed by components of secondary systems of vehicles traversing an environment can be received which may include event metrics or be indicative of events (such as an implementation of a safety response). Such metrics may be defined by algorithm output continuity data, algorithm output feasibility data, and/or algorithm output tracking data. The log data can be utilized to test candidate safety systems to determine test event metrics. Validation of the candidate safety system components can be performed based on aggregated event metrics (such as aggregated over a fleet) meeting various criteria.

Abstract: An agricultural vehicle includes a vision system. The vision system includes multiple cameras, a radar transceiver, and a controller. The multiple cameras are configured to produce image data of an area proximate the agricultural vehicle. The radar transceiver is configured to produce radar data of the area proximate the agricultural vehicle. The controller is configured to obtain the image data and the radar data, and combine the image data and the radar data to produce combined image and radar data. The combined image and radar data accounts for dust clouds in the area proximate the agricultural vehicle. The controller is also configured to present the combined image and radar data to an operator of the agricultural vehicle.

Abstract: The invention is notably directed to computer-implemented method of planning motion of a vehicle. The method comprises receiving (S20) real-time signals as to positions of N traffic participants. At each time step of multiple time steps, the method plans (S50) motion for the vehicle by computing (S30) states of each of the N traffic participants according to the signals received (S20). Said states include current states, which are estimated for each of the N traffic participants, as well as future states of each of the participants, wherein the future states are predicted over a prediction horizon T. This is achieved using an interaction-aware model of the N traffic participants. This model is designed to cause the method to recursively compute (S32-S38), at said each time step, the states of each of the N traffic participants according to a hierarchical list. The N traffic participants are ordered in the list from a most determinative one to a least determinative one of the N traffic participants.

Abstract: Vehicles and related systems and methods are provided for predicting a future maneuver expected to be executed by a driver. One method involves determining a combined probability for a potential maneuver based on constituent probabilities corresponding to different vehicle state variables, and environmental conditions using one or more tuning parameters specific to the respective combination of maneuver and vehicle state variable, determining an adjusted probability for the potential maneuver based at least in part on the combined probability and one or more contextual state variables corresponding to a current operating context for the vehicle, adapted to driver behavior and driving style, identifying the potential maneuver as an expected maneuver to be executed by a driver of the vehicle based on the adjusted probability, and automatically initiating one or more actions in a manner that is influenced by the expected maneuver.

Abstract: Described herein are examples of a system that processes information describing movement of a vehicle at a time related to a potential collision to reliably determine whether a collision occurred and/or one or more characteristics of the collision. In response to obtaining information regarding a potential collision, data describing movement of the vehicle before and/or after a time associated with the potential collision is analyzed to determine whether the collision occurred and/or to determine one or more collision characteristic(s). The analysis may be carried out at least in part using a trained classifier that classifies the vehicle movement data into one or more classes, where at least some the classes are associated with whether a collision occurred and/or one or more characteristics of a collision. If a collision is determined to be likely, one or more actions may be triggered based on the characteristic(s) of the collision.

Abstract: A vehicle deceleration assistance apparatus executes a deceleration assistance control to assist a deceleration of a vehicle before the vehicle arrives at a deceleration assistance target point to turn left or right. The apparatus executes the deceleration assistance control of a first level as a deceleration assistance level of assisting the deceleration of the vehicle when first and second conditions are satisfied. The first condition is a condition that a target point distance between the vehicle and the deceleration assistance target point is equal to or shorter than a predetermined distance, and blinkers are activated. The second condition is a condition that the blinkers activated for changing traffic lanes continues being activated. The apparatus executes the deceleration assistance control of a second level lower than the first level until a predetermined time elapses since the first condition becomes satisfied while the second condition is satisfied.

Abstract: An apparatus and method for protecting a passenger of a vehicle that may minimize impact energy transmitted to a passenger by realizing rotation, position change, and space securing of an interior seat according to sensor detection of an external impact to a vehicle. The apparatus for protecting a passenger includes at least one seat movable in a length direction of the vehicle and rotatable disposed inside a vehicle, a plurality of sensing units installed in the vehicle and outputting a collision signal in case of a vehicle collision, and a controller determining a direction and location of a collision in the vehicle in case of the vehicle collision and controlling the at least one seat to be selectively moved and/or rotated according to the direction and location of the collision.

Abstract: The control device controls a vehicle towing a trailer. The control device is configured to determine whether or not a user is present in the trailer when a shift range is in the parking range. The control device is configured to ignore a shift range switching operation by a driver when the shift range switching operation is performed while a user is present in the trailer.

Abstract: A method and an apparatus for collaborative end-to-end large model-oriented self-driving trajectory decision-making are provided. The method includes: processing an RGB image from ego vehicle, an RGB image from surrounding vehicle, and an RGB image from road-side by using a first feature extraction network to obtain a first image feature, a second image feature, and a third image feature, respectively; fusing first image feature, second image feature, and third image feature to obtain an image fusion feature; processing point cloud data of road-side to obtain a road-side point cloud feature; processing image fusion feature and road-side point cloud feature to obtain a first BEV feature and a second BEV feature; fusing first BEV feature and second BEV feature to obtain a fused BEV feature; and fusing prompt information and fused BEV feature to obtain text information, and then processing text information to obtain an ego vehicle trajectory decision-making result.

Abstract: A method for creating a road model for planning a trajectory of an ego vehicle, includes capturing a vehicle environment with at least one environment capturing sensor. Objects are detected in the vehicle environment. The method includes producing a grid map with a plurality of grid cells and entering the detections into the grid map wherein the detections are enlarged prior to being entered. The method also includes determining at least one path through the grid map which consists only of vacant grid cells. The at least one path is gradually scanned, wherein detections are determined orthogonally to a scanning direction of the path on both sides. The method further includes assigning the detections along the at least one path to road boundaries and creating the road model based on the previously determined information.

Abstract: Disclosed are a vehicle and a vehicle position calculation method. The vehicle includes an image sensor.

Abstract: Systems, methods and instrumentalities for a distributed detect and avoid (DM) framework for unmanned vehicles, such as unmanned aerial vehicles (UAVs). The systems, methods and instrumentalities may include a wireless transmit/receive unit (WTRU) associated with a vehicle. The WTRU may include a memory and a processor. The processor may be configured to store a trajectory of the vehicle and to send a message indicative of a conflict between the trajectory of the vehicle and a trajectory of another vehicle. The processor may be configured to receive a message from the other vehicle that is indicative of one or more conflicts and to determine a list that includes the vehicle(s) associated with the one or more conflicts. The processor may be configured to determine a resolution that addresses the conflict(s) associated with the list.

Abstract: Collision/fall reporting and alert systems and methods for micromobility vehicles include at least one proximity sensor, a speed sensor, at least one tilt sensor, a global positioning system, at least one warning device, a communication device, and a controller in communication with the at least one proximity sensor, the speed sensor, the at least one tilt sensor, the global positioning system, the at least one warning device, and the communication device.

Abstract: A method for providing a rider with a dynamic environmental awareness includes: receiving data from a set of sensors; correcting data; identifying a set of regions in the data; and processing the set of regions to detect a set of objects. In variants, the method can additionally include stabilizing the objects detected from the set of regions.

Abstract: In various examples, a hazard detection system plots hazard indicators from multiple detection sensors to grid cells of an occupancy grid corresponding to a driving environment. For example, as the ego-machine travels along a roadway, one or more sensors of the ego-machine may capture sensor data representing the driving environment. A system of the ego-machine may then analyze the sensor data to determine the existence and/or location of the one or more hazards within an occupancy grid—and thus within the environment. When a hazard is detected using a respective sensor, the system may plot an indicator of the hazard to one or more grid cells that correspond to the detected location of the hazard. Based, at least in part, on a fused or combined confidence of the hazard indicators for each grid cell, the system may predict whether the corresponding grid cell is occupied by a hazard.

Abstract: A field of awareness (FOA) system provides an operator of a vessel with intuitive object detection and positioning information. The system may comprise an FOA cloud server and an FOA unit. The FOA cloud server may be configured to perform a machine learning training operation to modify an FOA model based on a location-based relationship between training radar data and truth data. The FOA unit may be disposed on the vessel and may comprise processing circuitry configured to apply radar data to the FOA model to perform a comparison to determine a matched model signature, an associated matched object type, and an icon representation for the object of interest. The processing circuitry also be configured to control the display device to render the icon representation of the object at a position relative to a representation of the vessel based on the relative object position.

Abstract: An electronic device is provided. The electronic device includes a housing, a first camera module, a second camera module, a camera housing, and a supporting plate coupled to the camera housing, the camera housing includes a first barrier disposed between the first camera module and the second camera module, an accommodating part extending in a direction perpendicular to the supporting plate to surround the first camera module and the second camera module, a first opening exposed to the outside of the housing, and a second opening exposed to the outside of the housing, includes a covering part covering the first camera module and the second camera module, and a supporting member disposed inside the accommodating part to be in contact with at least one of the first camera module and the second camera module, the accommodating part is integrally formed with the covering part.

Abstract: A method of avoiding a collision based on an occupant position includes determining the occupant position based on occupant detection information, determining a collision range with an other vehicle based on occupant position information, controlling a collision avoidance sensitivity increment based on a rear-end collision range with the other vehicle, and activating a collision avoidance operation to avoid a collision with the other vehicle based on the collision avoidance sensitivity increment.

Abstract: The present disclosure relates to an apparatus and a method for controlling a vehicle, and, particularly, an apparatus and a method for controlling a vehicle capable of preventing a collision accident in advance by expanding a detection area of a vehicle by monitoring a lower end of a parked/stopped vehicle by adjusting a rotation angle of a sensor attached to the lower end of the vehicle on a front side and predicting a situation having a risk for a collision that may occur due to a blind spot in advance can be provided.

Abstract: A driving assistance apparatus sets a driving condition of a vehicle, based on a risk of surrounding environment that includes an object around the vehicle. The driving assistance apparatus includes a forward-risk calculator, a backward-risk calculator, and a driving-condition setter. The forward-risk calculator is configured to calculate a forward risk corresponding to a risk of a collision with a leading vehicle that travels ahead of the vehicle. The backward-risk calculator is configured to calculate a backward risk corresponding to a risk of a collision with a trailing vehicle that travels behind the vehicle. The driving-condition setter is configured to set the driving condition of the vehicle, based on the forward risk and the backward risk.

Abstract: A target tracking device to estimate a position of a target with high accuracy will be provided. The target tracking device is provided with a communication device and a processor. The communication device performs communication with a plurality of observation satellites that observe the target. The processor executes a selection of satellites, a setting of a schedule and an estimation. The selection of satellites includes selecting two or more selected satellites that observes the target among the plurality of observation satellites. The setting of the schedule includes determining an observation schedule for each of the two or more selected satellite to observe the target and transmitting an observation request signal that represents the determined observation schedule to a corresponding selected satellite. The estimation includes estimating the position of the target based on two or more pieces of high-precision observation information respectively observed by the two or more selected satellites.

Abstract: A method is provided for detecting regions of high curvature on a curve. The method comprises receiving a curve function and automatically arc length parameterizing the curve function. The local average curvature over the arc length parameterized curve function is automatically computed. One or more regions where the local average curvature turns at least a predetermined angle over a given interval are automatically indicated. The indicated regions are then output.

Abstract: A vehicle control system includes a setting unit to sense a plurality of forward vehicles positioned ahead of a subject vehicle in a driving direction, to classify each of the forward vehicles as a far-away vehicle or a near-by vehicle, and to set each of the far-away vehicles as an interest vehicle, a receiving unit to receive braking information of each of the interest vehicles from the respective interest vehicles, and a control unit to control braking of the subject vehicle based on the braking information of each of the interest vehicles received by the receiving unit.

Abstract: A vehicle travel assistance method and a travel assistance device for a vehicle include determining whether or not a route-following lane change that is a lane change for traveling along a set travel route can be assisted with autonomous lane change control, and when determining that the route-following lane change cannot be assisted with the autonomous lane change control, notifying a driver that a lane change with the autonomous lane change control cannot be made, and prohibiting the autonomous lane change control from assisting a lane change in a direction opposite to a direction in which the vehicle moves during the route-following lane change.

Abstract: A driving support apparatus assists driving of a vehicle by performing control of the vehicle corresponding to a blind spot. A driving support apparatus stores risk estimation information for calculating a risk estimation value indicating a height of a risk of a blind spot, and determines a plurality of blind spots as one conglomerate risk when the plurality of blind spots are detected in front of a vehicle and satisfy a predetermined condition. When the conglomerate risk exists, the driving support apparatus calculates a risk estimation value indicating the height of the risk in each of the plurality of blind spots on the basis of the risk estimation information, and determines a control end position for ending the control of the vehicle corresponding to the blind spot and a target passing speed of the control end position of the vehicle on the basis of the risk estimation value.

Abstract: In some examples, a system receives sensor data from sensors on board a vehicle. Based at least on the sensor data indicating an anomaly has occurred and is affecting a travel path of the vehicle, an uncertainty threshold is compared with an uncertainty value associated with a prediction model. For instance, the uncertainty value may be indicative of a difference between a predicted value predicted by the prediction model and an actual measured value related to at least one operation parameter of the vehicle. Based at least on determining that the anomaly has occurred and that the uncertainty value is within the uncertainty threshold, sending, by the system, a communication for obtaining an updated prediction model.

Abstract: Provided is a communication device that includes a wireless communication receiver that performs, with an external device, a first wireless communication for acquiring first information concerning a moving distance of the communication device and a second wireless communication that possibly has collision with the first wireless communication, and a processor that specifies a moving distance correlation value related to the moving distance. The processor acquires an acceleration of the communication device, specifies the moving distance correlation value based on the first information that the wireless communication receiver acquires from the external device, and specifies the moving distance correlation value based on the acceleration of the communication device in a case determining that a first condition is present. In the first condition, acquisition of the first information from the external device is possibly interrupted by the collision more than predetermined.

Abstract: Methods and systems are provided that include one or more sensors configured to obtain sensor data pertaining to both a driver of a vehicle and an environment surrounding the vehicle; and a processor that is coupled to the one or more sensors and that is configured to at least facilitate determining, using the sensor data, when the driver is incapacitated; determining, using the sensor data, when a threat is detected for the vehicle; and taking action to avoid the threat when the driver is incapacitated and the threat is detected, via instructions provided by the processor.

Abstract: A numerical controller uses specifications to control position-controlled axes of a production machine and determines a current group of position setpoint values and groups of position setpoint values expected for a forecast horizon. The numerical controller checks for the risk of a collision between at least one element moved by the position-controlled axes and at least one other element. The numerical controller carries out the same check for the expected groups. If there is no risk of collision, it stores the expected groups in a braking path memory and uses the current group. If there is the risk of a collision, it changes the axes along a path to a standstill defined by the braking path memory and braking is effected along a path which has been previously checked for the risk of a collision and for which no risk of a collision has been detected.

Abstract: A computer includes a processor and a memory, and the memory stores instructions executable by the processor to receive first environmental data recorded by an environmental sensor on board a vehicle, receive nonenvironmental data recorded on board the vehicle independently of the first environmental data, add a plurality of annotations derived from the nonenvironmental data to the environmental data, and train a machine-learning program to process second environmental data by using the first environmental data as training data and the annotations as ground truth for the first environmental data.

Abstract: Disclosed are an autonomous driving control apparatus for controlling autonomous driving based on feature points of another vehicle, and a method thereof. The autonomous driving control apparatus may obtain information about a surrounding object, may extract one or more feature points corresponding to the object through the information about the surrounding object, may determine whether there is a risk of collision with the surrounding object based on the extracted feature point, and may control autonomous driving of the autonomous vehicle in consideration of the surrounding object having the risk of collision with the autonomous vehicle.

Abstract: Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

Abstract: A collision avoidance system includes a periphery monitoring system which detects vehicles in proximity to a subject vehicle by use of a sensor, an approaching vehicle notifying system which communicates with another vehicle in proximity to the subject vehicle in vehicle-to-vehicle communication, and a detected vehicle comparison/determination system which is connected to the periphery monitoring system and the approaching vehicle notifying system, determines common vehicles detected by both the periphery monitoring system and the approaching vehicle notifying system, and controls the periphery monitoring system and the approaching vehicle notifying system.

Abstract: A method for preventing vehicle collision applied in an electronic device obtains a first image in the driving direction of a vehicle using the method (method vehicle), and detects a driving route of other vehicles in the first image, and takes one of the other vehicles in the first image as a target vehicle when it satisfies a first condition. The first condition comprises a vehicle being in the same lane as the method vehicle and having an opposing driving direction. The electronic device further detects whether a detectable distance between the method vehicle and the target vehicle is less than a preset distance, and generates a warning or a control command when the detectable distance is less than the preset distance.

Abstract: A vehicle traveling control method, includes: predicting traveling paths of candidate vehicles within the sensing range of a current vehicle; determining a target competing vehicle competing with the current vehicle from the candidate vehicles, where the target competing vehicle is a vehicle having a path intersection with the traveling path of the current vehicle; determining the traveling strategy combinations of the current vehicle and the target competing vehicle according to preset traveling variations and current traveling status of the current vehicle and the target competing vehicle; and determining a target traveling strategy combination that meets preset safe traveling conditions from the traveling strategy combinations, and controlling the traveling of the current vehicle according to the target traveling strategy combination.

Abstract: A surrounding environment recognition device recognizes a surrounding environment around a vehicle. A traveling control unit centrally controls a whole of the entire vehicle. An obstacle presumer presumes presence of an obstacle ahead of the vehicle based on a behavior distribution of preceding vehicles recognized by the surrounding environment recognition device, and estimates a position and an area where the obstacle is present when the presence of the obstacle is presumed. A traveling path calculator calculates candidates for traveling path areas along which the vehicle is expected to travel while avoiding collision with the presumed obstacle. A traveling path selector selects a traveling path area from among the calculated traveling path areas and sets the selected traveling path area. The traveling control unit controls the vehicle to travel along the set traveling path area.

Abstract: To achieve an objective to enable a plurality of management business operators managing space objects flying in space, to share and carry out danger analysis efficiently. In a space traffic management system, a plurality of space traffic management devices are connected to each other via a communication line. Each of the plurality of space traffic management devices includes a space information recorder, a danger alarm device, a danger analysis device, a danger avoidance action assist device, and a security device. The space information recorder includes a space object ID, orbital information, and public condition information; and a business device ID and public condition information. The plurality of space traffic management devices have data format compatibility and share the space object ID and the business device ID, and share orbital information corresponding to the space object ID among business devices that comply with the public condition information.

Abstract: A method includes obtaining, by a processing device, radar sensor data from a driving environment of an autonomous vehicle (AV). The radar sensor data corresponds to a field-of-view (FOV) of a radar sensor of the AV. The method further includes identifying, by the processing device from the radar sensor data, a potential occlusion within the driving environment, obtaining, by the processing device, non-radar sensor data from the driving environment, the non-radar sensor data corresponding to a FOV of a non-radar sensor of the AV, determining, by the processing device from the non-radar sensor data, whether the potential occlusion is a false occlusion, and in response to determining that the potential occlusion is a false occlusion, removing, by the processing device, the false occlusion from the FOV of the radar sensor.

Abstract: A reactive path planner for vehicles is disclosed. The reactive path planner, based on a nominal path from A to B, generates alternative parallel paths which are displaced by a predefined lateral distance from the nominal path using constrained quintic polynomials. Constraints are imposed on the alternative paths to ensure safety and comfort based on dynamic and mechanical feasibilities of the vehicle. A cost function is applied to the nominal path and alternative paths select the path with the least cost. The reactive path planner achieves a complete path planning solution with high computational efficiency, even in highly cluttered and dynamic environments.

Abstract: An apparatus includes: a first sensor configured to provide a first input; a second sensor configured to provide a second input; and a processing unit configured to receive the first input from the first sensor, and a second input from the second sensor; wherein the processing unit is configured to determine a first probability of a first predicted event, and a second probability of a second predicted event, wherein the first predicted event and the second predicted event are associated with an operation of the vehicle; and wherein the processing unit is configured to calculate a risk score based on the first probability of the first predicted event, and based on the second probability of the second predicted event.

Abstract: Disclosed is a dynamic regulation method for a lane changing decision point of a CAV dedicated lane in a diverging area of an expressway, applied to the diverging area of the expressway in which the CAV dedicated lane is provided at an inner side of a road. Vehicles traveling in the CAV dedicated lane are all CAVs. Both the CAVs and human-driven vehicles can travel in ordinary lanes. The method calculates the lane changing decision points of diversion vehicles in the CAV dedicated lane at current time using corresponding algorithms based on a relationship between the lane changing decision points of the CAV dedicated lane and traffic efficiency and a traffic safety.

Abstract: A system for creating synthetic data for testing an autonomous system, comprising at least one hardware processor adapted to execute a code for: using a machine learning model to compute a plurality of depth maps based on a plurality of real signals captured simultaneously from a common physical scene, each of the plurality of real signals are captured by one of a plurality of sensors, each of the plurality of computed depth maps qualifies one of the plurality of real signals; applying a point of view transformation to the plurality of real signals and the plurality of depth maps, to produce synthetic data simulating a possible signal captured from the common physical scene by a target sensor in an identified position relative to the plurality of sensors; and providing the synthetic data to at least one testing engine to test an autonomous system comprising the target sensor.

Abstract: A computer-implemented method comprises sensing an environment of the ego-agent that includes at least one other agent. The method predicts possible behaviors of the at least one other agent based on the sensed environment, and plans trajectories of the ego-agent for each possible behavior of the at least one other agent to generate a set of planned trajectories. The method proceeds with determining an actual trajectory of the ego-agent, and comparing the determined actual trajectory of the ego-agent with each of the planned trajectories of the ego-agent and determining a planned trajectory with a largest similarity to the actual trajectory of the ego-agent. Subsequently, a perceived situation as perceived by the ego-agent based on a particular predicted possible behavior of the predicted possible behaviors corresponding to the planned trajectory with the largest similarity is determined. The method executes an action in an assistance system based on the determined perceived situation.

Abstract: Provided is an advanced driver assist system (ADAS) and a vehicle having the same. The ADAS includes: a communicator configured to communicate with a plurality of other vehicles; an obstacle detector configured to detect an obstacle in a surrounding and output obstacle information about the detected obstacle; and a controller configured to acquire distance information about a distance to a second vehicle travelling in the surrounding of the first vehicle among the obstacles based on the obstacle information detected by the obstacle detector during a cruise control mode, acquire travel information and position information of a third vehicle travelling in the surrounding of the second vehicle based on information received through the communicator, and controlling acceleration and deceleration based on the distance information with respect to the second vehicle, the travel information of the third vehicle, and the position information of the third vehicle.

Abstract: A radar system is provided that includes a compression component configured to compress blocks of range values to generate compressed blocks of range values, and a radar data memory configured to store compressed blocks of range values generated by the compression component.

Abstract: Examples described may related to an imaging sensor used by a vehicle, including a light sensor. The light sensor comprises a plurality of cells aligned in a plurality of horizontal rows and a plurality of vertical columns. The apparatus further includes an optical system configured to provide the light sensor with a field of view of an external environment of the apparatus. Additionally, the system includes a processing unit configured to: divide the plurality of horizontal rows of the light sensor into one or more enabled rows and one or more disabled rows; obtain image data from the light sensor by sampling one or more cells in the one or more enabled rows; and store the received image data in a memory.

Abstract: A system for motion planning for a vehicle includes at least one vehicle sensor for determining information about an environment surrounding the vehicle and a controller in electrical communication with the at least one vehicle sensor. The controller is programmed to perform a plurality of measurements of a remote vehicle using the at least one vehicle sensor. The plurality of measurements includes at least a plurality of position measurements of the remote vehicle. The controller is further programmed to determine a risk score for each of a plurality of location cells in an environment surrounding the remote vehicle based at least in part on the plurality of measurements of the remote vehicle. The controller is further programmed to adjust a planned path of the vehicle based at least in part on the risk score of each of the plurality of location cells in the environment surrounding the remote vehicle.

Abstract: A vehicle control apparatus acquires a first collision risk based on a relative distance and a relative speed between an obstacle ahead of a vehicle and the vehicle, outputs a first control instruction for autonomously applying a braking force to the vehicle based on the first collision risk, acquires a second collision risk into which the first collision risk is updated after the braking force is autonomously applied to the vehicle, outputs a second control instruction for autonomously applying a force regarding steering to the vehicle based on the second collision risk, and outputs a third control instruction for controlling the braking force to be generated on a wheel portion of the vehicle based on the second collision risk after the force regarding the steering is autonomously applied to the vehicle.

Abstract: A system includes an interface configured to receive sensor data corresponding to a potential hazard associated with a travel path of a vehicle. The system also includes an obstacle database including probability distributions of potential obstacles. The system further includes one or more processors coupled to the interface and configured to generate a probability index associated with the potential hazard and to determine whether to modify the travel path based on the probability index and the probability distributions.

Abstract: A device and a method that prevent a tracking target tracked by a mobile device from deviating from a field of view at a fork, thereby enabling reliable tracking, are provided. When a control parameter determination unit of a mobile device cannot discriminate one of a plurality of routes constituting a fork that a tracking target selects and moves along, the control parameter determination unit calculates a goal position for bringing the tracking target within a viewing angle of the mobile device and a goal posture at the goal position, and generates a control parameter including the calculated goal position and goal posture. The control parameter determination unit calculates a position and posture that enable the tracking target to be within the viewing angle of the mobile device regardless of a route that the tracking target selects and moves along.