Abstract: A method is disclosed for vehicular operation on a road comprising a road network configured to communicate with one or more vehicles on the road, the method comprising sending a signal from a first vehicle to the road network, the signal comprising an intended path of the first vehicle on the road; receiving the signal at the road network; and adjusting at least one of a speed and a path of a second vehicle with respect to the road in response to the signal.

Abstract: Aspects concern a method for controlling a braking of a vehicle. The method including detecting a braking situation, determining a classification of the braking situation, selecting a braking profile based on the determined classification, and applying a deceleration based on the selected braking profile to maintain a safety distance based on the selected braking profile.

Abstract: A method includes generating an initial radar track using radar data and initial radar parameters and an initial camera track using image angular position data, initial camera parameters, and the radar range data in combination with calculating correction parameters to be applied to one of the radar data and the image data by comparing positions for the object from the initial radar track and the initial camera track, the first correction parameters being selected so that, when applied to the data from the other of the radar and the camera, to generate a first corrected track, a degree of correspondence between the first corrected track and the track of the other of the radar and camera is higher than a degree of correspondence between the initial radar track and the initial camera track.

Abstract: A driving support method supports driving of a host-vehicle in a traveling scene in which a host-vehicle track on which the host-vehicle travels and a first other vehicle track on which a first other vehicle travels intersect with each other at an intersecting point. Whether the host-vehicle can enter the intersecting point is determined based on a shielding time during which a second other vehicle shields the first other vehicle track to the intersecting point and a required entry time from when the host-vehicle starts entering the intersecting point to when the host-vehicle finishes entering the intersecting point.

Abstract: A method of path planning for a host vehicle includes: receiving host vehicle, environmental and obstacle information; calculating one or more projected host vehicle locations; computing a projected obstacle location for each obstacle; and determining a collision potential between each projected host vehicle location and each projected obstacle location. Until a maximum number of steps is reached, and while at least one projected host vehicle location has an associated collision potential below a collision threshold, the method further includes repeating the calculating, computing and determining steps.

Abstract: A head-up display and a method for operating a head-up display for a motor vehicle. Virtual objects may be assigned to parts of the environment of the motor vehicle, where a virtual reference feature is obtained, the orientation of which is defined on the basis of a roadway that is or can be used by a vehicle. An orientation of the motor vehicle may be determined in relation to the virtual reference feature. A virtual object may be displayed when the part of the environment to which it is assigned lies within a field of view for the head-up display, wherein a horizontal position of the object that is displayed is defined in the field of view on the basis of the relative orientation to the virtual reference feature.

Abstract: In a vehicle contact avoidance assist system (1) for providing assistance in avoiding an obstacle located ahead of a vehicle including a contact avoidance control unit (15) configured to perform an obstacle avoidance operation upon detecting an obstacle located ahead of the vehicle, the obstacle avoidance operation including a steering of the steerable wheel via the steering actuator so as to avoid the obstacle, the contact avoidance control unit is configured to apply a restriction on the obstacle avoidance operation depending on a detected gripping state detected by a steering wheel gripping state detection unit (8).

Abstract: The present disclosure provides a camera signal monitoring apparatus and method, the camera signal monitoring apparatus including a processor, which includes a vehicle information input unit for receiving a vehicle speed and a yaw rate signal of a vehicle; a camera information input unit for receiving a camera signal including a vehicle speed and a yaw rate signal from a vehicle front camera; and a monitoring unit for calculating a vehicle driving trajectory using the vehicle speed and the yaw rate signal of the vehicle input from the vehicle information input unit, calculating a reference curvature value based on the calculated vehicle driving trajectory, and determining a reliability by comparing the calculated reference curvature value with a curvature value calculated by the camera signal input from the camera information input unit.

Abstract: A controller causes a host vehicle to decelerate when a velocity of an oncoming vehicle corresponding to a position of the oncoming vehicle distant from a stationary object by a predetermined distance is greater than or equal to a velocity threshold corresponding to the position of the oncoming vehicle distant from the stationary object by the predetermined distance in a case in which a passing position is present within a predetermined region, and causes the host vehicle to keep the velocity or accelerate when the velocity of the oncoming vehicle corresponding to the position of the oncoming vehicle distant from the stationary object by the predetermined distance is less than the velocity threshold corresponding to the position of the oncoming vehicle distant from the stationary object by the predetermined distance in the case in which the passing position is present within the region.

Abstract: A blind spot information acquisition device includes: a processor configured to: acquire sounds in an area around a vehicle, infer positions of occurrence of the sounds that have been acquired, acquire information relating to objects in the area around the vehicle, and determine that there is a sound occurring in a blind spot in a case in which a sound source in the positions of occurrence of the sounds cannot be identified from the information relating to objects in the area around the vehicle that has been acquired.

Abstract: An example operation includes one or more of detecting, by a transport, that the transport is approaching a traffic control marking on a road, providing a notification related to the detecting to one or more occupants of the transport, receiving from one or snore other transports, at a server, one or more indications of a crossing of the traffic control marking by the transport, determining, by the server, a consensus of the crossing based on the one or more indications, and performing, by the server, an action to correct the crossing.

Abstract: A method for operating a steering system of a vehicle, wherein an actuator is provided for generating a moment at a steering handle of the vehicle, wherein the following steps are carried out: generating the moment up to a maximum moment if the maximum moment is enabled, and up to a lower limited moment if the maximum moment is limited, identifying a vehicle situation of the vehicle, enabling the maximum moment if the vehicle situation is identified as being a boarding and/or deboarding situation in order to brace the steering handle, and limiting the maximum moment if the vehicle situation is identified as being driving operation of the vehicle.

Abstract: A method performed by a vision control system for supporting in low light conditions in surroundings of a moving vehicle, object detection by at least a first on-board rearward- and/or sideward-facing image capturing device. The vision control system captures a surrounding located rearward and/or sideward of the moving vehicle with support from the at least first image capturing device. The vision control system further determines light conditions in the surrounding. Moreover, the vision control system provides with support from at least a first light source, when the light conditions fulfill insufficient light criteria, a light output illuminating a ground region of the surrounding to facilitate object detection by the at least first image capturing device. The disclosure also relates to a vision control system, a vehicle comprising such a vision control system, and a respective corresponding computer readable storage medium.

Abstract: System, method, and device for controlling a vehicle. In one example, the system includes an electronic processor configured to capture, via a camera, a first image, determine, within the first image, a road traffic factor, and generate, based on sensor information from one or more sensors of the vehicle, a second image depicting an environment surrounding the vehicle. The second image includes the road traffic factor. The electronic processor is also configured to, determine, based on the detected road traffic factor and the second image, a predicted trajectory of a traffic participant proximate to the vehicle, and generate a steering command for the vehicle based on the predicted trajectory.

Abstract: A system includes at least partially autonomous vehicles, at least partially separated interconnected roadways, and a management system. Each of the vehicles is configured to cooperate with another vehicle or an area controller. The management system is configured to receive requests to transport, which may have respective start points and respective destinations. Additionally, the management system is configured, responsive to receiving the request, to assign a vehicle to fulfill the request. The assigned vehicle is configured to transport a person from the respective start point, at least in part via the interconnected roadways, to the respective destination.

Abstract: Embodiments of the present application provide a collision detection method and apparatus based on an autonomous vehicle, a device and a storage medium, where the method includes: acquiring first point cloud data of each obstacle in each region around the autonomous vehicle, where the first point cloud data represents coordinate information of the obstacle and the first point cloud data is based on a world coordinate system; converting the first point cloud data of the each obstacle into second point cloud data based on a relative coordinate system, where an origin of the relative coordinate system is a point on the autonomous vehicle; determining, according to the second point cloud data of the each obstacle in all regions, a possibility of collision of the autonomous vehicle. A de-positioning manner for collision detection is provided, thereby improving the reliability and stability of collision detection.

Abstract: A vehicle may include a primary system for generating data to control the vehicle and a secondary system that validates the data and/or other data to avoid collisions. For example, the primary system may localize the vehicle, detect an object around the vehicle, predict an object trajectory, and generate a trajectory for the vehicle. The secondary system may localize the vehicle, detect an object around the vehicle, predict an object trajectory, and determine a likelihood of a collision of the vehicle with the object. A simulation system may generate simulation scenarios that test aspects of the primary system and the secondary system. Simulation scenarios may include simulated vehicle control data that causes the primary system to generate a driving trajectory and simulated object data that causes the secondary system to determine a collision.

Abstract: Detecting out-of-model scenarios for an autonomous vehicle including: determining, based on first sensor data from one or more sensors, an environmental state relative to the autonomous vehicle, wherein operational commands for the autonomous vehicle are based on a selected machine learning model, wherein the selected machine learning model comprises a first machine learning model; comparing the environmental state to a predicted environmental state relative to the autonomous vehicle; and determining, based on a differential between the environmental state and the predicted environmental state, whether to select a second machine learning model as the selected machine learning model.

Abstract: In various examples, a sequential deep neural network (DNN) may be trained using ground truth data generated by correlating (e.g., by cross-sensor fusion) sensor data with image data representative of a sequences of images. In deployment, the sequential DNN may leverage the sensor correlation to compute various predictions using image data alone. The predictions may include velocities, in world space, of objects in fields of view of an ego-vehicle, current and future locations of the objects in image space, and/or a time-to-collision (TTC) between the objects and the ego-vehicle. These predictions may be used as part of a perception system for understanding and reacting to a current physical environment of the ego-vehicle.

Abstract: A safety system and a method for localizing at least one object having a control and evaluation unit have at least one radio location system. The radio location system has at least three arranged radio stations. Position data of the object can be determined by means of the radio location system and can be transmitted to the control and evaluation unit. At least three radio transponders are arranged at the object, each arranged spaced apart from one another and the three radio transponders form different points on a plane and unambiguously define the plane in space. The control and evaluation unit is configured to compare the position data of the radio transponders and to form checked position data of the object. The control and evaluation unit is configured to form orientation data of the object from the position data of the radio transponders.

Abstract: A vehicle control device includes a communication unit configured to communicate with a plurality of autonomous driving vehicles configured to perform autonomous traveling, and a processor. The processor is configured to, when an abnormality occurs in or around at least one first autonomous driving vehicle among the plurality of autonomous driving vehicles, determine a travel instruction for controlling traveling of the first autonomous driving vehicle, transmit the travel instruction to the first autonomous driving vehicle via the communication unit, set a priority representing the degree of the priority in which an instruction operator is notified of the travel instruction in the order determined according to the content of the abnormality, notify any one of at least one instruction terminal of the determined travel instruction in the order of highest priority, and receive a result of checking the determined travel instruction from the instruction terminal.

Abstract: Methods of determining which kinematic model an autonomous vehicle (AV) should use to predict motion of a detected moving actor are disclosed. One or more sensors of the AV sensors will detect a moving actor. The AV will assign one or more probable classes to the actor, and it will process the information to determine a kinematic state of the actor. The system will query a library of kinematic models to return one or more kinematic models that are associated with each of the probable classes. The system will apply each of the returned kinematic models to predict trajectories of the actor. The system will then evaluate each of the forecasted trajectories of the actor against the kinematic state of the actor to select one of the returned kinematic models to predict a path for the actor. The system will then use the predicted path to plan motion of the AV.

Abstract: An item drop box sensor system for detecting items deposited within a drop box may be configured to detect movement of an item deposit tray and to detect items deposited within the drop box. The drop box sensor system may comprise one or more tray movement sensors for detecting movement of the deposit tray, one or more item detection sensors configured to detect items passing into the drop box via the deposit tray, and an onboard controller for selectively activating the various sensors to conserve power and for transmitting data indicative of the status of the drop box to a central server configured for scheduling item pickups for various geographically spaced drop boxes.

Abstract: A vehicle may receive sensor data captured by a sensor, determine that the sensor data represents an object in the environment, and determine a collision probability associated with a predicted collision between the vehicle and the object. Based at least in part on the collision probability, a position of a headrest of the vehicle may be determined relative to a head of an occupant of the vehicle. The headrest may be adjusted in one or more directions prior to occurrence of the predicted collision to minimize injury to the occupant due to the collision.

Abstract: A vehicle driving assist apparatus of the invention starts a collision avoidance steering assist control to automatically steer the vehicle to avoid a collision of the vehicle with the obstacle in response to a driver performing a collision avoidance steering operation for avoiding the collision when there is a possibility that the vehicle collides with the obstacle. The vehicle driving assist apparatus cancels the collision avoidance steering assist control in response to the driver performing a counter collision avoidance steering operation against automatically steering the vehicle intended to be achieved by the collision avoidance steering assist control after a first predetermined time elapses from starting the collision avoidance steering assist control.

Abstract: A system and method for estimating and communicating a path of travel of a reference vehicle by road side equipment (RSE) that includes establishing communication between the RSE and an on-board equipment of the reference vehicle and receiving vehicle parameters of the reference vehicle from the on-board of the reference vehicle. The system and method also include estimating the path of travel of the reference vehicle based on the vehicle parameters of the reference vehicle and environmental parameters determined by the RSE. The system and method further include establishing communication between the RSE and an on-board equipment of a target vehicle and communicating the estimated path of travel of the reference vehicle from the RSE to the target vehicle, wherein a probability of collision between the reference vehicle and the target vehicle is determined based on the estimated path of travel of the reference vehicle.

Abstract: A method for operating an automated vehicle includes controlling by one or more computing devices an autonomous vehicle; receiving by one or more computing devices sensor data from the vehicle corresponding to moving objects in a vicinity of the vehicle; receiving by one or more computing devices road condition data; and determining by one or more computing devices undesirable locations related to the moving objects. The undesirable locations related to the moving objects for the vehicle are based at least in part on the road condition data. The step of controlling the vehicle includes avoiding the undesirable locations.

Abstract: Provided herein is a system of a vehicle that comprises one or more sensors, one or more processors, and memory storing instructions that, when executed by the one or more processors, causes the system to perform: selecting a trajectory along a route of the vehicle; predicting a trajectory of another object along the route; adjusting the selected trajectory based on a predicted change, in response to adjusting the selected trajectory, to the predicted trajectory of the another object, the predicted change to the predicted trajectory of the another object being stored in a model; determining an actual change, in response to adjusting the selected trajectory, to a trajectory of the another object, in response to an interaction between the vehicle and the another object; updating the model based on the determined actual change to the trajectory of the another object; and selecting a future trajectory based on the updated model.

Abstract: Among other things, techniques are described for predicting how an agent (e.g., a vehicle, bicycle, pedestrian, etc.) will move in an environment based on prior movement, the road network, the surrounding objects and/or other relevant environmental factors. One trajectory prediction technique involves generating a probability map for an agent's movement. Another trajectory prediction technique involves generating a trajectory lattice, for an agent's movement. In addition, a different trajectory prediction technique involves multi-modal regression where a classifier (e.g., a neural network) is trained to classify the probability of a number of (learned) modes such that each model produces a trajectory based on the current input.

Abstract: Systems, methods, computer-readable media, and apparatuses for providing hazard detection and broadcast functions are provided. In some examples, sensor data may be captured by a mobile device, vehicle, or the like. The data may be used to detect a hazard, identify a type of hazard, and the like. One or more users or groups of users for notification of the hazard may be identified and one or more notifications may be transmitted to users within the group.

Abstract: This disclosure pertains to a method for operating a terminal (10) in a wireless communication network. The method comprises performing a Listen-Before-Talk, LBT, procedure on at least one LBT communication link of a set of LBT communication links, wherein performing the LBT procedure is based on 475 information received by the terminal (10), the received information pertaining to operational conditions of the LBT communication links of the set of LBT communications links. The disclosure also pertains to related devices and methods.

Abstract: A transportation vehicle with at least one first sensor for capturing environment data, at least one second sensor for capturing transportation vehicle data, a communication module for establishing a data connection with another transportation vehicle, a driving system for automated driving of the transportation vehicle, at least one output element for a visible/audible warning signal, and a control unit. The control unit determines a predicted trajectory of the transportation vehicle, determines a predicted path of the transportation vehicle and receives a predicted trajectory and vehicle geometry data of the other transportation vehicle via the data connection, determines a predicted path of the other transportation vehicle, determines a possible collision of the transportation vehicle with the other transportation vehicle, and in response to a possible collision, outputs a warning signal by the at least one output element and/or carries out an automated driving maneuver by the driving system.

Abstract: An advanced driver assistance system configured to implement one or more automotive V2V applications designed to assist a driver in driving a Host Motor-Vehicle. The advanced driver assistance system is configured to be connectable to an automotive on-board communication network to communicate with automotive on-board systems to implement one or different automotive functionalities aimed at assisting the driver in driving the Host Motor-Vehicle, controlling the Host Motor-Vehicle, and informing the driver of the Host Motor-Vehicle of the presence of Relevant Motor-Vehicles deemed to be relevant to the driving safety of the Host Motor-Vehicle.

Abstract: A lane keep assist device is configured to perform lane keep assist control for making a host vehicle travel along a lane, and preventing the host vehicle from departing from the lane. The lane keep assist device includes an electronic control device configured to detect presence or absence of another vehicle, present in a vicinity of the host vehicle, which have a gradual decrease in a distance from the host vehicle, and when the other vehicle is detected, the electronic control device configured to set virtual line extending along front-rear direction of the detected other vehicle at position away by first predetermined distance in right-left direction of the other vehicle from lateral side of the detected other vehicle, and to specify the lane based on the set virtual line to perform the lane keep assist control.

Abstract: A non-transitory computer readable storage medium has instructions executed by a processor to obtain the relative speed between a first traffic object and a second traffic object. The separation distance between the first traffic object and the second traffic object is received. The relative speed and the separation distance are combined to form a quantitative measure of hazard encountered by the first traffic object. The obtain, receive and combine operations are repeated to form cumulative measures of hazard associated with the first traffic object. The cumulative measures of hazard are analyzed to derive a first traffic object safety score for the first traffic object.

Abstract: A velocity trajectory generation method and apparatus, and a storage medium are provided. The method includes: setting starting point time, intermediate point time and terminal point time of a velocity trajectory to be generated, wherein the velocity trajectory includes a first velocity sub-trajectory and a second velocity sub-trajectory; generating multiple first velocity sub-trajectories corresponding to a starting point velocity between the starting point time and the intermediate point time, according to the starting point velocity and multiple intermediate point velocities; and generating, for each of the first velocity sub-trajectories, multiple second velocity sub-trajectories between the intermediate point time and the terminal point time according to multiple terminal point velocities. A velocity trajectory which is more in line with a human driving characteristic may be generated, the comfort level of a passenger may be improved, and an algorithm may be simplified.

Abstract: The present disclosure relates to a method for determining an action for collision avoidance in a craft.

Abstract: An apparatus for assistance avoidance steering is provided. The apparatus includes a processor configured to perform avoidance steering control based on Rear Wheel Steering (RWS) control when a head-on collision risk is sensed, and a storage configured to store data and an algorithm runnable by the processor. The avoidance steering control is based on the algorithm.

Abstract: The present disclosure generally relates to generating emergency vehicle warnings, automatic control of autonomous vehicles based upon the emergency vehicle warnings. More particularly, the present disclosure relates to generating data representative of emergency vehicle warnings and alternate autonomous vehicle routing based upon real-time information related to an emergency vehicle. The information related to the emergency vehicle may include emergency vehicle origination location data, emergency vehicle current location data, emergency vehicle route data, and/or emergency vehicle destination location data. An emergency vehicle warning and/or alternate vehicle routing for autonomous vehicles may be generated based further on information related to an autonomous vehicle. In one aspect, an emergency vehicle may wirelessly communicate with the autonomous vehicle and/or an insurance provider remote server.

Abstract: Systems and methods are disclosed for estimating slipperiness of a road surface. This estimate may be obtained using an image sensor mounted on a vehicle. The estimated road slipperiness may be utilized when calculating a risk index for the road, or for an area including the road. If a predetermined threshold for slipperiness is exceeded, corrective actions may be taken. For instance, warnings may be generated to human drivers that are in control of driving vehicle, and autonomous vehicles may automatically adjust vehicle speed based upon road slipperiness detected.

Abstract: Systems and methods for interactions between an autonomous vehicle and one or more external observers include virtual models of drivers the autonomous vehicle. The virtual models may be generated by the autonomous vehicle and displayed to one or more external observers, and in some cases using devices worn by the external observers. The virtual models may facilitate interactions between the external observers and the autonomous vehicle using gestures or other visual cues. The virtual models may be encrypted with characteristics of an external observer, such as the external observer's face image, iris, or other representative features. Multiple virtual models for multiple external observers may be simultaneously used for multiple communications while preventing interference due to possible overlap of the multiple virtual models.

Abstract: A processing platform may obtain sensor data associated with a vehicle and manual input data associated with the vehicle. The processing platform may determine, based on the sensor data, automated control information. The processing platform may determine, based on the sensor data and the manual input data, a parameter associated with the vehicle. The processing platform may determine, based on the automated control information, a control rating associated with the parameter. The processing platform may determine whether the control rating satisfies a threshold for a period of time. The processing platform may cause, based on determining that the control rating satisfies the threshold for the period of time, at least one action to be performed.

Abstract: Provided is a vehicle control device configured to execute specific control while at the same time sequentially switching the specific control that defines an operation to be executed by each of a plurality of surrounding environment acquisition devices configured to acquire information on a surrounding environment of a vehicle, a recognition/determination ECU configured to generate a path on which the vehicle is to travel, and an integrated control ECU configured to control the vehicle based on the generated path along with an elapse of time since detection of an anomaly, when the anomaly is detected in any one of the plurality of surrounding environment acquisition devices, the recognition/determination ECU, and the integrated control ECU.

Abstract: A driving assistance device to properly recognize a relative positional relationship between mobile objects without the use of map information. The driving assistance device includes a relative position judgment section for judging a relative positional relationship of an object of interest and a first neighboring object relative to a second neighboring object, based on object-of-interest information and neighbor information, to make a judgment as a first judgment on a relative positional relationship between the object of interest and the first neighboring object, based on the aforementioned judgment result.

Abstract: A system includes a computer having a processor and a memory storing instructions executable by the processor to determine a braking distance based on a gap distance between a primary vehicle and a second vehicle in an adjacent lane, and based on a speed of the second vehicle in the adjacent lane. The instructions include instructions to actuate a braking system of the primary vehicle when the primary vehicle is the braking distance from a third vehicle in a same lane as the primary vehicle.

Abstract: A device may include a memory storing instructions and processor configured to execute the instructions to receive information relating to a plurality of vehicles in an area. The device may be further configured to use a trained machine learning model to determine a likelihood of collision by one or more of the plurality of vehicles; identify one or more relevant vehicles of the plurality of vehicles that are in danger of collision based on the determined likelihood of collision; and send an alert indicating the danger of collision to at least one of the identified one or more relevant vehicles.

Abstract: A system, method and storage medium for providing an emergency vehicle alert includes first device transmitting EV data including a current location of an EV to a management server, management server receiving the EV data from the first device, the management server determining a geofence for the EV at least based on the received EV data and geographical map data near the EV, and management server transmitting the determined geofence to a second device. The first device is associated with the EV, and the second device is associated with the another vehicle.

Abstract: Disclosed is a method and a system for retrieving a location of a base point of a wheeled vehicle in a local coordinate system of a tridimensional sensor mounted on the vehicle. The method includes acquiring point cloud frames while the wheeled vehicle is moving along a straight path and a curved path and a point cloud representative of a portion of the vehicle, computing a main direction vector, a main direction line and a location of an instantaneous centre of rotation of the wheeled vehicle in the local coordinate system, and retrieving the location of the base point.

Abstract: A trajectory determination method for a vehicle is provided. A target vehicle trajectory is determined from among multiple candidate vehicle trajectories by considering, for each of the candidate vehicle trajectories, presence or absence of a front obstacle, presence or absence of a potentially-colliding obstacle, and a condition related to lane change, so as to enhance driving safety of the vehicle.

Abstract: A vehicle includes a lane generator that is configured to receive information that describes a first lane portion and a second lane portion and determine that a discontinuity is present. The lane generator obtains a sensor output and detects presence of a nearby vehicle in the first lane portion. A classification for the nearby vehicle is identified by analyzing the sensor output, and is used to select a vehicle kinematics model. The lane generator determines paths for a simulated vehicle from the first lane portion to the second lane portion using the vehicle kinematics model. A third lane portion is determined based on the paths such that the third lane portion defines a traversable route from the first lane portion to the second lane portion in accordance with the vehicle kinematics model. An automated vehicle control system generates control outputs based in part on the third lane portion.