Abstract: A vehicle, navigation system of the vehicle, and method for observing an environment of the vehicle. The navigation system includes a sensor and a processor. The sensor obtains a detection from an object located in an environment of the vehicle at a with-detection direction with respect to the sensor that includes the detection. The processor determines a no-detection direction that does not include the detection, assigns an empty space likelihood to an occupancy grid of the sensor along the no-detection direction, and generates a map of the environment using the occupancy grid.

Abstract: A method and apparatus for controlling a first vehicle autonomously are disclosed. For instance, one or more processors may plan to maneuver the first vehicle to complete an action and predict that a second vehicle will take a particular responsive action. The first vehicle is then maneuvered towards completing the action in a way that would allow the first vehicle to cancel completing the action without causing a collision between the first vehicle and the second vehicle, and in order to indicate to the second vehicle or a driver of the second vehicle that the first vehicle is attempting to complete the action. Thereafter, when the first vehicle is determined to be able to take the action, the action is completed by controlling the first vehicle autonomously according to whether the second vehicle begins to take the particular responsive action.

Abstract: A driving support apparatus according to the invention estimates the position of a moving body by controlling a position estimation unit when the tracking-target moving body leaves a first area or a second area to enter a blind spot area and detects the position of the moving body by controlling a position detection unit when the moving body leaves the blind spot area to enter the first area or the second area. In this manner, the trajectory of the tracking-target moving body is calculated so that the trajectory of the moving body detected in the first area or the second area and the trajectory of the moving body estimated in the blind spot area are continuous to each other and driving support is executed based on the calculated trajectory of the tracking-target moving body.

Abstract: The present invention extends to methods, systems, and computer program products for formulating lane level routing plans. In general, aspects of the invention are used in motorized vehicles to guide a driver to a terminal vehicle configuration according to a lane level routing plan that balances travel time with routing plan robustness. A lane level routing plan can be based on terminal guidance conditions (e.g., exiting a highway in the correct off ramp lane), statistical patterns of lanes themselves, current vehicle state, and state of the local environment near the vehicle. Lane level routing plans can be communicated to the driver with audio, visual, and/or haptic cues. Lane level routing plans can be revised online and in (essentially) real-time in response to changing conditions in the local environment (e.g., a trailing vehicle in a neighboring lane has decided to increase speed).

Abstract: A target intention predicting method including a dataset obtaining step and a calculating and map mapping step is provided. A host vehicle positioning dataset of a host vehicle and a plurality of target datasets of a target are obtained. Each of the target datasets corresponds to each of a plurality of time points of a time line, and each of the target datasets includes a target position and a target velocity. The host vehicle positioning dataset is mapped to a map. The target position at the last one of the time points is mapped to the map. An updated velocity of the target is calculated according to the target velocities of the target datasets, and the updated velocity is mapped to the map to predicting a target future position of the target on the map at a future time point according to the updated velocity.

Abstract: Various examples are directed to systems and methods for dispatching autonomous vehicles. A service arrangement system may receive error data describing an error state at a first autonomous vehicle executing a first transportation service. The first transportation service may include moving a payload from a transportation service start point to a transportation service end point. The service arrangement system may determine, using the error data, a first property of the first autonomous vehicle associated with the error state and select a second autonomous vehicle that does not have the first property. The service arrangement system may send to the second autonomous vehicle a transportation service request requesting that the second autonomous vehicle travel to a rendezvous location to meet the first autonomous vehicle and transport the payload from the rendezvous location to the transportation service end point.

Abstract: In one embodiment, a method includes, by a computing system associated with a vehicle, receiving sensor data from one or more sensors of the vehicle, wherein the sensor data is based on an environment of the vehicle, identifying, based on the sensor data, one or more objects in the environment, generating, based on the one or more objects, a set of points that represent the environment, wherein each object has one or more corresponding points in the set of points, and each of the points is associated with one or more features associated with the corresponding object, generating a prediction for at least one of the objects in the environment or the vehicle by processing the set of points using a machine-learning model, and causing the vehicle to perform one or more operations based on the prediction.

Abstract: Navigation systems can identify objects in an environment and generate representations of those objects. A representation of an articulated vehicle can include two segments rotated relative to each other about a pivot, with a first segment corresponding to a first portion of the articulated vehicle and the second segment corresponding to a second portion of the articulated vehicle. The articulated object can be tracked in the environment by generating estimated updated states of the articulated agent based on previous states and/or measured states of the object using differing motion model updates for the differing portions. The estimated updated states may be determined using one or more filtering algorithms, which may be constrained using pseudo-observables.

Abstract: An information processing apparatus of a moving body includes: a sensing information acquisition part which acquires sensing information indicative of a situation of the outside of the moving body by a sensor mounted on the moving body for detecting an object; a traveling obstruction determination part which determines a mode of other moving body which travels near the moving body using the sensing information; and a movement request generation part which controls a movement request transmitted to the moving body using a determination result of the mode of the other moving body.

Abstract: A collision prediction apparatus includes a radar-detection target position detection section, a pattern matching execution section that detects an image detection target, an image-detection target position detection section, an identical target determination section that determines that the radar detection target and the image detection target are an identical target when a positional relationship between the both targets becomes a predetermined relationship; a collision prediction section that predicts whether the own vehicle is likely to collide with an identical target as an object, and a support execution section that performs driving support when a collision between the own vehicle is predicted. In the apparatus, the collision prediction section predicts whether the radar detection target, as the object, is likely to collide with the own vehicle, under conditions that the object is turning in a direction approaching the own vehicle, and that the image detection target can no longer be detected.

Abstract: A vehicle radar control apparatus may include: a camera configured to capture a forward image in a traveling direction of a traveling vehicle; one or more radar sensors each configured to irradiate a radar signal from the traveling vehicle, and receive a radar signal reflected and returned from the neighboring vehicle; and a control unit configured to generate traveling information including one or more of distance, direction and speed of the traveling vehicle with respect to the neighboring vehicle by analyzing the forward image captured by the camera and the radar signal received by the radar sensor.

Abstract: A travel control device comprising: a control unit configured to control travel of a vehicle; a first acquisition unit configured to acquire information regarding the surroundings of the vehicle; and a second acquisition unit configured to acquire vehicle information regarding another vehicle traveling in the same direction as the vehicle in a different lane from the lane that the vehicle is traveling in with at least a part of the other vehicle forward of the vehicle, the vehicle information regarding the other vehicle being included in the information regarding the surroundings of the vehicle acquired by the first acquisition unit, wherein, if the vehicle information regarding the other vehicle fulfills a condition, the control unit, in accordance with a state of approach of the vehicle to the other vehicle, performs control so that the vehicle decelerates.

Abstract: A method and apparatus for establishing a device connection applied to a first device with a camera are provided. The method includes acquiring an image of a second device by the first device through the camera, recognizing the type of the second device through the acquired image of the second device, acquiring a device list corresponding to the type of the second device through an IoT server, and identifying the second device in the device list, acquiring a unique identifier of the second device in the current IoT environment, and using the unique identifier of the second device to initiate a connection request to the second device to establish a connection with the second device. The method may automatically establish a connection between devices with less operation of the devices.

Abstract: Systems and methods are provided for vehicle navigation. In one implementation, a processing device may be configured to obtain a planned driving action for accomplishing a navigational goal of a host vehicle; receive sensor data from an environment surrounding the host vehicle; identify a target vehicle moving in the environment and a velocity of the target vehicle; calculate a stopping distance and a predicted trajectory for the target vehicle; calculate a planned trajectory for the host vehicle corresponding to the planned driving action; identify an intersection of the planned trajectory for the host vehicle with the predicted trajectory for the target vehicle; determine a braking action of the host vehicle to comply with a safety requirement; and cause the braking action to be applied to decelerate the host vehicle to change the planned trajectory, until the changed trajectory does not intersect the predicted trajectory of the target vehicle.

Abstract: A computer-implemented method for controlling a vehicle system of a host vehicle merging into a lane. The method includes determining an actual distance between the host vehicle and the one or more remote vehicles. The actual distance is a longitudinal distance between the host vehicle and the one or more remote vehicles. The method includes determining a safe distance for merging into the lane based on a relative position of the host vehicle to the one or more remote vehicles, a speed of the host vehicle, and a speed of the one or more remote vehicles. The safe distance is a second longitudinal distance between the host vehicle and the one or more remote vehicles. The method includes controlling the vehicle system of the host vehicle to assist a merge maneuver by the host vehicle according to the actual distance and the safe distance.

Abstract: A surrounding situation display method of detecting a surrounding situation around a host vehicle with an autonomous driving function and displaying the detected surrounding situation, includes displaying, in a varying display bar that has a prescribed display frame and displays an indication position within the display frame in synchronization with movement of an attention target, the indication position having moved to one endpoint of the varying display bar as a timing when an action of the host vehicle is changed by the autonomous driving function.

Abstract: A pedestrian protection apparatus includes: an active sensor configured to sense a dynamic behavior of a vehicle; a passive sensor configured to sense a collision of the vehicle; and a pedestrian protection module configured to: predict a possibility of a pedestrian collision in response to active information received from the active sensor, the pedestrian collision being a collision of the vehicle that involves a pedestrian; adjust a threshold value for sensing the collision of the vehicle determined by passive information received from the passive sensor in response to predicting the possibility of the pedestrian collision; and deploy a protection module in response to determining the pedestrian collision using the adjusted threshold value and the passive information received from the passive sensor.

Abstract: A dangerous act resolution apparatus comprises: an acquisition part that acquires peripheral vehicle specific information; a position detection part that detects a position of the vehicle; a vehicle-to-vehicle distance measurement part that measures a vehicle-to-vehicle distance; a travel speed measurement part that measures a travel speed of the vehicle; a travel direction detection part that detects a travel direction of the vehicle; and a dangerous act detection part that judges that a dangerous act occurs when a situation in which the vehicle-to-vehicle distance is shorter than a preset first threshold and the travel speed exceeds a preset second threshold occurs within a predetermined time; and transmits dangerous act detection information according to the peripheral vehicle specific information, the position, the travel speed and the travel direction to the management center apparatus.

Abstract: A collision determination apparatus includes an acquisition section, a setting section, a target object information detection section, a target object path prediction section, an own vehicle path prediction section, and a collision determination section. The acquisition section acquires detection information based on a reflected wave from a search device. The setting section sets filter characteristics of a filtering process used when the detection information is filtered. The target object information detection section detects a position of a target object using the filtered detection information. The target object path prediction section predicts a path of the target object based on changes in the position of the target object detected by the target object information detection section. The own vehicle path prediction section predicts a path of an own vehicle. The collision determination section makes a determination of a collision between the own vehicle and the target object.

Abstract: According to one aspect of the invention, there is provided a method for determining a travel route of a robot, comprising the steps of: identifying at least one obstacle with respect to a position of a robot; calculating an obstacle radius in which the at least one obstacle has influence, with reference to at least one of information on motion properties of the at least one obstacle and information on a relationship with at least one other obstacle associated with the at least one obstacle; and determining an optimum travel route of the robot with reference to the calculated obstacle radius and a task assigned to the robot.

Abstract: A method includes obtaining map data associated with a map of a geographic location including one or more roadways, the map including a first submap represented by a first local Euclidean space and a second submap represented by a second local Euclidean space. A route that includes a first roadway in the first submap and a second roadway in the second submap is determined using a first projection between a global coordinate system and the first local Euclidean space and a second projection between the global coordinate system and the second local Euclidean space. The route is provided to an autonomous vehicle (AV) for driving on the first roadway and the second roadway.

Abstract: A predictive controller controls a system under uncertainty subject to constraints on state and control variables of the system. At each control step, the predictive controller solves an inequality constrained nonlinear dynamic optimization problem including probabilistic chance constraints representing the uncertainty to produce a control command, and controls an operation of the system using the control command. The predictive controller solves the dynamic optimization problem based on a two-level optimization that alternates, until a termination condition is met, propagation of covariance matrices of the probabilistic chance constraints within the prediction horizon for fixed values of the state and control variables with optimization of the state and control variables within the prediction horizon for fixed values of the covariance matrices.

Abstract: Techniques are provided for operation of a vehicle using multiple motion constraints. The techniques include identifying an object using one or more processors of a vehicle. The vehicle has a likelihood of collision with the object that is greater than a threshold. The processors generate multiple motion constraints for operating the vehicle. At least one motion constraint includes a minimum speed of the vehicle greater than zero to avoid a collision of the vehicle with the object. The processors identify one or more motion constraints for operating the vehicle to avoid a collision of the vehicle with the object. The processors operate the vehicle in accordance with the identified motion constraints.

Abstract: A map construction method, an electronic device and a readable storage medium are disclosed. The map construction method includes: obtaining three-dimensional point cloud data corresponding to observed objects in current target frame data, the observed objects including a feature object and a non-feature object; obtaining a feature parameter corresponding to the feature object based on three-dimensional point cloud data corresponding to the feature object, the feature parameter being used to indicate a position and a size of the feature object; and adjusting a point cloud density of three-dimensional point cloud data corresponding to the non-feature object to a preset value, to construct a map according to the feature parameter and the three-dimensional point cloud data of which the point cloud density is adjusted.

Abstract: A computer-implemented method can comprise determining, by a system operatively coupled to a processor, points of interest comprising image coordinates in a set of images captured by an optical camera of a moving vehicle, determining, by the system, whether a multi-match exists in the set of images, in response to determining that the multi-match does not exist, rejecting, by the system, the points of interest, in response to determining that the multi-match exists, determining, by the system, whether the points of interest represent a false-positive determination of a stationary object, in response to determining that the points of interest are in motion and correspond to a false-positive, rejecting, by the system, the points of interest, and in response to determining that the points of interest are stationary and do not correspond to a false-positive, initiating, by the system, collision avoidance to avoid a stationary object corresponding to the points of interest.

Abstract: A control system is provided to improve riding comfort of a human-powered vehicle. The control system includes an electronic controller and a receiver. The electronic controller is configured to control a first electric component of a first human-powered vehicle. The receiver is configured to receive first reference information related to a vehicle that differs from the first human-powered vehicle. The electronic controller is configured to control the first electric component based on the first reference information.

Abstract: Embodiments described herein may provide a method for generating a local hazard warning polygon and establishing a quality score thereof. Methods may include: receiving a plurality of probe data points from a plurality of probes within a mapped region, where each probe data point includes location information and weather condition information; generating, based on a plurality of probe data points indicating an adverse weather condition, a local hazard warning condition polygon including a plurality of local hazard warning condition vertices; receiving weather conditions at each of a plurality of map points within the mapped region; correlating each local hazard warning condition vertex with a respective map point within the mapped region; and establishing a quality score of the local hazard warning condition polygon based on a proportion of the local hazard warning condition vertices indicating an adverse weather condition agreeing with a weather condition at a respective correlated map point.

Abstract: A vehicular control system includes a forward viewing camera and a non-vision sensor. The control, responsive to processing of captured non-vision sensor data and processing of frames of captured image data, at least in part controls the equipped vehicle to travel along a road. The control, responsive at least in part to processing of frames of captured image data, determines lane markers on the road and determines presence of another vehicle traveling along the traffic lane ahead of the equipped vehicle and determines a trajectory of the other vehicle relative to the equipped vehicle. The control stores a trajectory history of the determined trajectory of the other vehicle relative to the equipped vehicle as the other vehicle and the equipped vehicle travel along the traffic lane.

Abstract: In response to perceiving a moving object, one or more possible object paths of the moving object are determined based on the prior movement predictions of the moving object, for example, using a machine-learning model, which may be created based on a large amount of driving statistics of different vehicles. For each of the possible object paths, a set of trajectory candidates is generated based on a set of predetermined accelerations. Each of the trajectory candidates corresponds to one of the predetermined accelerations. A trajectory cost is calculated for each of the trajectory candidates using a predetermined cost function. One of the trajectory candidates having the lowest trajectory cost amongst the trajectory candidates is selected. An ADV path is planned to navigate the ADV to avoid collision with the moving object based on the lowest costs of the possible object paths of the moving object.

Abstract: The present invention provides a camera signal monitoring apparatus and method, the camera signal monitoring apparatus including a vehicle information input unit receiving a vehicle speed and a yaw rate signal of a vehicle; a navigation information input unit receiving a road curvature signal provided in a high precision map; a camera information input unit receiving a camera signal including a vehicle speed and a yaw rate signal from a vehicle front camera; and a monitoring unit calculating a reference curvature value based on at least one of the vehicle speed and the yaw rate signal of the vehicle, which are input from the vehicle information input unit, or the road curvature signal from the navigation information input unit, and determining a reliability by comparing the calculated reference curvature value with a curvature value calculated using the camera signal input from the camera information input unit.

Abstract: Presented are target object detection systems for deriving host vehicle velocities, methods for making/using such systems, and motor vehicles with host vehicle velocity estimation capabilities. A method of automating operation of vehicles includes an electronic transmitter of a vehicle's target object detection system emitting electromagnetic signals, and an electronic receiver receiving multiple reflection echoes caused by each electromagnetic signal reflecting off target objects within proximity of the vehicle. A vehicle controller determines a relative velocity vector for each target object based on these reflection echoes. The relative velocity vectors are assigned to discrete vector clusters. The controller estimates a host vehicle velocity vector as an average of the relative velocity vectors in the vector cluster containing the most relative velocity vectors and having the largest spatial spread.

Abstract: A vehicle control system including: a recognizer that recognizes a target in the vicinity of a subject vehicle; a first processor that repeatedly performs a process of determining a first target speed, which is a target speed of the subject vehicle in the future, at a first period on the basis of the target recognized by the recognizer and a state of the subject vehicle; a second processor that repeatedly performs a process of determining a second target speed, which is a target speed of the subject vehicle in the future, at a second period shorter than the first period on the basis of the first target speed determined by the first processor, the target recognized by the recognizer, and the state of the subject vehicle; and a running controller that controls acceleration/deceleration of the subject vehicle on the basis of at least one of the first target speed determined by the first processor and the second target speed determined by the second processor.

Abstract: The present disclosure relates to robot path planning. Depth information of a plurality of obstacles in an environment of a robot are obtained at a first time instance. A static distance map is generated based on the depth information. A path is computed for the robot based on the static distance map. At a second time instant, depth information of one or more obstacles is obtained. A dynamic distance map is generated based on the one or more obstacles, wherein for each obstacle that satisfies a condition: a vibration range of the obstacle is computed based on a position of the obstacle and the static distance map, and the obstacle is classified as a dynamic obstacle or a static obstacle based on a criterion associated with the vibration range. A repulsive speed of the robot is computed based on the dynamic distance map to avoid the dynamic obstacles.

Abstract: A method for managing a change in a physical property of a vehicle due to an external object that is attached to the vehicle, the method may include receiving information regarding the external object and a relationship between the external object and the vehicle; wherein at least part of the information is sensed information that is sensed by a sensor; determining, by a vehicle computer and based on the information, an effect of the external object on the vehicle; and responding to the effect of the external object on the vehicle.

Abstract: An unmanned aircraft system includes an aircraft control system that enables the safe operation of multiple unmanned aerial vehicles in the same airspace, through the use of a decentralized air traffic management system. The decentralized air traffic management system is robust against loss of communication between the unmanned aerial vehicle and does not require a centralized ground control system to coordinate the vehicles.

Abstract: A travel assistance method selects a merging destination vehicle that will travel in front or behind a host vehicle when the host vehicle merges into an adjacent lane, based on a history of whether other vehicles traveling in the adjacent lane allowed merging of a first preceding vehicle traveling in front of the host vehicle on a host lane and locations of the other vehicles traveling in the adjacent lane in a lane direction within a section in which the merging into the adjacent lane from the host lane is possible.

Abstract: Provided is a moving object detector capable of acquiring a position history of a moving object that is less affected by the behavior of a subject vehicle. In a moving object detector, a moving-object relative position acquiring unit acquires position coordinates of a moving object expressed in a subject-vehicle-based coordinate system that is based on the position of a subject vehicle. A subject-vehicle state quantity acquiring unit acquires the state quantity of the subject vehicle. A coordinate converter generates a history of position coordinates of the moving object expressed in a moving-object-based coordinate system that is based on the position of the moving object, on the basis of the position coordinates of the moving object expressed in the subject-vehicle-based coordinate system, and the state quantity of the subject vehicle.

Abstract: A system and method for automatically detecting a vehicle collision and taking action in response to the vehicle collision is disclosed. The vehicle collision can be detected by analyzing information from sensors onboard a vehicle, in a mobile device disposed within the vehicle or from roadway sensors. When a collision is detected, an insurance provider can automatically open a new insurance claim. The provider may also use sensed information to detect damaged components of a vehicle and provide information about the damaged components to a vehicle repair facility.

Abstract: Embodiments herein relate to a method for handling a driver's use of an object displaying device comprised in a vehicle. The driver's use of the object displaying device is monitored. Based on the monitoring, a likelihood that the driver has detected a representation of the object when using the object displaying device is determined. The representation of the object is visible to the driver in the object displaying device, and the object is located in the surroundings of the vehicle.

Abstract: A method, computer system, and a computer program product for preemptive collision mitigation is provided. The present invention may include calculating a future position of a first vehicle based on carprobe data from a first vehicle, wherein the carprobe data contains neural data of an operator of the first vehicle. The present invention may also include calculating a distance between the future position of the first vehicle and a future position of a second vehicle. The present invention may then include determining the calculated distance between the future position of the first vehicle and the future position of the second vehicle is below a threshold distance.

Abstract: A traveling control apparatus is configured to control automated driving traveling of a vehicle based on a set automated driving level. The traveling control apparatus comprises: an acquisition unit configured to acquire traveling scene information that specifies a traveling scene of the vehicle; and a control unit configured to perform offset control to offset a traveling position of the vehicle in a vehicle width direction to increase a distance to another vehicle traveling side by side with the vehicle. The control unit performs the offset control by setting one of a first mode and a second mode based on at least one of the traveling scene information and the automated driving level.

Abstract: An automatic driving assist apparatus includes a map information acquirer; an own vehicle position estimator; a route information input unit; a traveling environment information acquirer, a traveling route setting unit, an other-vehicle traveling route acquirer, and an automatic driving controller. The automatic driving controller further includes a target travel path generator, an other-vehicle detection determiner, and a relative vehicle speed determiner, an other-vehicle traveling route determiner, and an automatic traveling controller. The automatic traveling controller causes the own vehicle to travel following another vehicle along a target travel path generated by the target travel path generator in a case where the other-vehicle traveling route determiner determines that a traveling route of the other vehicle is set in a direction of a branch path.

Abstract: A method for determining event data including: sampling a first data stream within a first time window at a first sensor of an onboard vehicle system coupled to a vehicle, extracting interior activity data from the first data stream; determining an interior event based on the interior activity data; sampling a second data stream within a second time window at a second sensor of the onboard vehicle system; extracting exterior activity data from the second image stream; determining an exterior event based on the exterior activity data; correlating the exterior event and the interior event to generate combined event data; automatically classifying the combined event data to generate an event label; and automatically labeling the first time window of the first data stream and the second time window of the second data stream with the combined event label to generate labeled event data.

Abstract: Driver and pedestrian safety can be aided by systems and methods to provide identification and classification of objects in a vehicle travel path. Information about classified objects can be shared with a human driver to inform the driver about potentially hazardous conditions, or the information can be interpreted automatically by an operating system of the vehicle. In an example, a camera coupled to a vehicle can receive images from an image sensor. A computer system can use machine learning and neural network-based processing to identify an object present in the images and determine whether the object is a pedestrian. In an example, the computer system can process information from a region of interest in the images that comprises less than an entire field of view in the images.

Abstract: A vehicular control system includes a camera and a receiver disposed at the equipped vehicle. A control includes an image processor that processes image data captured by the camera to detect vehicles present within the field of view of the camera. The vehicular control system determines presence of another vehicle that constitutes a potential hazard existing exterior of the equipped vehicle responsive at least in part to a wireless communication originating from the other vehicle and received by the receiver. When the other vehicle enters the field of view of the camera, and responsive at least in part to the image processor processing image data captured by the camera, the control detects that the other vehicle is present within the field of view of the camera and controls at least one vehicle function of the equipped vehicle to mitigate collision with the other vehicle.

Abstract: An object of the vehicle control device according to the present invention is to provide a driver with acceleration/deceleration control of a vehicle with less discomfort even in a situation where correction of measurement of an inter-vehicle distance is required due to a temperature change or the like.

Abstract: A method and an apparatus for determining a vehicle speed computing a probability distribution of action intentions based on observation information of a surrounding object. Then, a probability redistribution of the different action intentions is computed based on travel times for the vehicle to travel from a current position to risk areas corresponding to the different action intentions, motion status variations of the surrounding object with the different action intentions are predicted based on the travel times for the vehicle to travel to the risk areas corresponding to the different action intentions. Finally, the travelling speed of the vehicle is determined based on the probability redistribution of the different action intentions, the motion status variations of the surrounding object with the different action intentions, and motion status variations of the vehicle under different travelling speed control actions.

Abstract: A computer includes a processor and a memory, the memory storing instructions executable by the processor to identify an initial lateral distance and an initial longitudinal distance of a host vehicle in a turn at an initiation of the turn, predict a heading angle of the host vehicle at a specified time after the initiation of the turn, predict a final lateral distance and a final longitudinal distance between the host vehicle and a target at the specified time based on the identified lateral distance, the identified longitudinal position, and the predicted heading angle, determine a lateral offset at a longitudinal time to collision based on the final lateral distance and the final longitudinal distance, and actuate a brake of the host vehicle according to a threat assessment based on the lateral offset.

Abstract: Embodiments of the present application provide a lane line processing method and a lane line processing device. The method can include: performing a binarization processing on a first image to obtain a binary image, the first image including lane line points and non-lane line points; performing a connected domain analysis on the binary image to obtain at least one connected domain in the binary image, the connected domain including a plurality of adjacent lane line points; determining lane line points in a group corresponding to a lane line, based on the connected domain; and obtaining representation information of the lane line corresponding to the group, by using the lane line points in the group.

Abstract: The invention relates to a method for operating a driver assistance system (2) of a motor vehicle (1) comprising a) sensing a plurality of vehicles (5a-5d) in the surroundings (6) of the motor vehicle (1) by means of a sensing device (3) of the driver assistance system (2); b) determining a respective driving parameter value for at least one driving parameter of the sensed vehicles (5a-5d) by means of a computing device (7) of the driver assistance system (2); c) categorizing the sensed vehicles (5a-5d) on the basis of the at least one driving parameter value, respectively determined for the sensed vehicles (5a-5d), in average vehicles (5a-5c) and in atypical vehicles (5d); d) collectively predicting an overall behaviour for a totality of the sensed average vehicles (5a-5c) on the basis of the driving parameter values determined for the average vehicles (5a-5c); and e) individually predicting a respective individual behaviour for the sensed atypical vehicles (5d) on the basis of the respective driving paramet