Abstract: Among other things, we describe techniques for adjusting lateral clearance for a vehicle using a multi-dimensional envelope. A trajectory is generated for the vehicle. A multi-dimensional envelope is generated indicating a drivable region for the vehicle and containing the trajectory. One or more objects are identified located along or adjacent to the trajectory. At least one dimension of the generated multi-dimensional envelope is adjusted to adjust a lateral clearance between the vehicle and the identified one or more objects. A control module of the vehicle navigates the vehicle along the multi-dimensional envelope.

Abstract: A method and corresponding device for the decentralized cooperative coordination of at least two vehicles includes: determining an abstract driving maneuver to realize at least one nominal driving maneuver by a first vehicle, determining driving maneuver information regarding the first vehicle's at least one abstract driving maneuver, transmitting the first vehicle's driving maneuver information to at least one further vehicle, calculating or reconstructing the first vehicle's nominal trajectory and/or nominal driving maneuver based on the received driving maneuver information by the further vehicle, comparing the first vehicle's reconstructed nominal trajectory and/or the reconstructed nominal driving maneuver with the further vehicle's nominal trajectory and/or nominal driving maneuver and, if a conflict exists between the nominal trajectory and/or the nominal driving maneuver of the first vehicle and the nominal trajectory and/or the nominal driving maneuver of the further vehicle, transmitting a cooperati

Abstract: A method of localizing a host member through sensor fusion includes capturing an input image with one or more optical sensors disposed on the host member and determining a location of the host member through a global positioning system (GPS) input. The method tracks movement of the host member through an inertial measurement unit (IMU) input, generates coordinates for the host member from the GPS input and the IMU input. The method compares the input image and a high definition (HD) map input to verify distances from the host member to predetermined objects within the input image and within the HD map input. The method continuously localizes the host member by fusing the GPS input, the IMU input, the input image, and the HD map input.

Abstract: A method of determining a navigation trajectory for an autonomous ground vehicle (AGV) is disclosed. The method may include receiving first Region of Interest (ROI) data associated with an upcoming trajectory path, and receiving predicted attributes associated with a future navigation trajectory for the upcoming trajectory path. The predicted attributes are derived based on map for the upcoming trajectory path. The method may further include modifying the predicted attributes based on environmental attributes extracted from first ROI data to generate modified attributes, and dynamically receiving a second ROI data associated with the upcoming trajectory path upon reaching the upcoming trajectory path. The method may further include predicting dynamic attributes associated with an imminent navigation trajectory for the upcoming trajectory path based on the second ROI data, and refining the modified attributes based on the one or more dynamic attributes to generate a final navigation trajectory.

Abstract: A system and method for automatically engaging an autonomous driving mode in a vehicle is disclosed. The method includes monitoring a driver and switching to the autonomous driving mode if an unsafe driving condition is detected. The method can include monitoring biometric data. The method can also include monitoring behavioral data using one or more kinds of vehicle sensors. The system and method ensure a vehicle is safely driven even if a driver experiences a health episode that could leave them unable to safely operate the vehicle.

Abstract: The present disclosure relates to a method, apparatus, and computer-readable storage medium for providing three-dimensional stereo sound to a vehicle to promote active safety and awareness to hazards. For instance, the present disclosure describes a method for providing three-dimensional stereo sound comprising receiving data signals from sensors positioned around an exterior of a vehicle, detecting a hazard based on the received data signals, determining characteristics of the detected hazard, generating an alert based on the determined characteristics of the detected hazard, and outputting the generated alert as the three-dimensional stereo sound via speakers arranged around an interior of the vehicle, the outputted alert communicating to a driver of the vehicle the determined characteristics of the detected hazard.

Abstract: A method for manufacturing a near-infrared sensor cover includes arranging a mask in a region of an undercoating layer formed on a rear surface of a base, the region being different from a heater formation region in which a heater is to be formed and different from a belt-shaped separation region extending along an edge of the heater formation region, forming a heat-generating film on the mask and the undercoating layer, the heat-generating film being made of the conductive heat-generating material, peeling, using a laser, the heat-generating film formed in the separation region, and removing the mask and the heat-generating film formed on the mask. The separation region has a width that is set to be smaller than a beam diameter of each of near-infrared rays transmitted from the transmitting portion.

Abstract: A method of tracking at least one emergency service provider is disclosed. An electronic history is compiled that includes at least one identifier of a service provider, at least one identifier of an event to which the service provider responded, and GPS data identifying the geographic location of the service provider at each time interval within the duration of the event. A user interface within which is displayed a first identifier of a first event is generated to a display device. A selection of the event identifier is received from a user. In response to the selection of the identifier, an aerial view of a geographic region within which the first event took place is generated. At least one icon is displayed in the aerial view representing the service provider at the geographic location corresponding to at least one time interval during the event.

Abstract: A vehicle electronic controller includes a peripheral obstacle identification section identifying obstacles near the vehicle, a blind spot region identification section identifying a blind spot region which is not in a detection range of the obstacle identification section, a region determination section which classifies the blind spot region into either a dangerous blind or a safe blind spot region and an obstacle region presumption section which presumes an obstacle presence region which is a region that a latent obstacle which is the latent obstacle which could be present at a previous time in the dangerous blind spot region which was classified at the previous time can be present at a present time, in which the region determination section determines that a region which overlaps with at least the obstacle presence region in the blind spot region that the blind spot region identification section identified is the dangerous blind spot region.

Abstract: Techniques for generation of an optimal trajectory for a vehicle include receiving, using one or more processors of the vehicle, an instruction for the vehicle to travel from an initial spatiotemporal location to a destination spatiotemporal location. One or more processors are used to generate a trajectory including travel segments. The trajectory begins at the initial spatiotemporal location and terminates at the destination spatiotemporal location. Each travel segment begins at a first spatiotemporal location and terminates at a second spatiotemporal location. Each travel segment is associated with operational metrics. The operational metrics are associated with navigating the vehicle from the first spatiotemporal location to the second spatiotemporal location. Each operational metric is optimized across the travel segments to generate the trajectory.

Abstract: A driving assist system executes driving assist control for avoiding a collision with a target ahead of a vehicle. The driving assist control operates when the target exists within an assist area. First and second roadway boundaries of a roadway area are located on first and second sides as viewed from the vehicle, respectively. A crossing target is the target crossing the roadway area ahead of the vehicle from the first side toward the second side. The assist area for the crossing target is an area between an assist start boundary located on the first side as viewed from the vehicle and an assist end boundary located on the second side as viewed from the vehicle. The driving assist system sets the assist end boundary at a position between the vehicle and the second roadway boundary of the roadway area.

Abstract: In various examples, sensor data representative of a field of view of at least one sensor of a vehicle in an environment is received from the at least one sensor. Based at least in part on the sensor data, parameters of an object located in the environment are determined. Trajectories of the object are modeled toward target positions based at least in part on the parameters of the object. From the trajectories, safe time intervals (and/or safe arrival times) over which the vehicle occupying the plurality of target positions would not result in a collision with the object are computed. Based at least in part on the safe time intervals (and/or safe arrival times) and a position of the vehicle in the environment a trajectory for the vehicle may be generated and/or analyzed.

Abstract: Systems and methods are presented herein for enabling a vehicle, configured to support autonomous vehicle operation, to change a location of the vehicle based on the detection of an impending impact with the vehicle. A starting location of the vehicle is determined while the vehicle is parked, unoccupied, and comprises an inactive powertrain. In response to determining a watchdog state is enabled, data corresponding to the location is accessed from within a threshold distance of the vehicle. An identifier and a trajectory of an object is determined. In response to determining that the trajectory corresponds to an impact path with the vehicle, an evasive route for the vehicle is determined that terminates at a safe location not subjected to the impending impact. An instruction to activate the vehicle powertrain and an autonomous mode of the vehicle to execute the identified evasive route is transmitted for the vehicle to process.

Abstract: This document describes target curvature estimation considering vehicle dynamics constraints. Some vehicle dynamics models use several kinematic states to predict the paths of targets identified by an object-tracking system. Rather than rely on predetermined industry measurements as the kinematic inputs to a model, an example system instead estimates some of these states using near real-time data output from a tracking filter. This can include estimating position and velocity states, as well as curvature and centripetal acceleration states. The example system is particularly suited at accurately predicting the curvature and centripetal acceleration states, which greatly improves the accuracy of the object-tracking system, and further improves safety in avoiding a target collision.

Abstract: A method for a base station in communication with a user device through a wireless communications network is described. The method includes communicating with a user device on a current frequency through a wireless communications network. The method may also include determining, based at least in part on a model, a probability that a higher capacity may be acquired by the user device on a frequency other than the current frequency; predicting a first recommended frequency for the user device that is likely to have a higher capacity than the current frequency; instructing the user device to scan the first recommended frequency; receiving an indication from the user device that the first recommended frequency has a higher capacity than the current frequency; and communicating with the user device on the first recommended frequency.

Abstract: An object-detection system for an automated vehicle includes an object-detector, a receiver, and a controller. The object-detector detects detectable-objects proximate to a host-vehicle. The receiver receives an indication of an object-presence from other-transmitters proximate to the host-vehicle. The controller is in communication with the object-detector and the receiver. The controller is configured to operate the host-vehicle to avoid interference with a hidden-object when the hidden-object is not detected by the object-detector and the object-presence is indicated by at least two instances of the other-transmitters.

Abstract: The techniques and systems herein enable estimated-acceleration determination for AEB. Specifically, for a potential collision, a determination is made as to whether the target of the potential collision is likely to be stopped prior to the potential collision (e.g., due to its own braking). One of a plurality of estimated-acceleration functions is then selected based on whether the target is likely to be stopped prior to the potential collision. Using the selected estimated-acceleration function, an estimated acceleration to avoid the potential collision is calculated. By selecting different estimated-acceleration functions based on whether targets are likely to be stopped prior to potential collisions, more-accurate estimated accelerations may be generated, thus enabling better collision avoidance and/or avoiding unnecessarily strong braking.

Abstract: A method for cut in maneuver alert, the method may include receiving by a vehicle computerized system of a vehicle, one or more cut in maneuver predictors, each cut in maneuver predictor is (a) indicative of a predicted cut in maneuver initiated by another vehicle, and is (b) generated by a machine learning process; obtaining sensed information regarding an environment of the vehicle; processing the sensed information, wherein the processing comprises searching for a cut in maneuver predictor; and finding the cut in maneuver predictor.

Abstract: Systems and methods are provided for improved pedestrian and vehicle safety along with systems and methods for obtaining or sharing data from surrounding mobile assets in the case of an occurrence of an event of interest, an impending event of interest or emergency situation.

Abstract: A method for determining rail vehicle location and identifying obstacles, which includes operations of transmitting, from at least two vehicle beacons on a first vehicle, a ranging signal to at least two external beacons; receiving, at the at least two vehicle beacons, a return signal from the at least two external beacons; and determining, based on the return signal from the at least two external beacons, a position of each of the external beacons with respect to the at least two vehicle beacons of the first vehicle.

Abstract: A method for controlling at least one industrial truck comprising determining a driving job using a superordinate control unit and sending the driving job from the superordinate control unit to a transceiver of the at least one industrial truck. The driving job is transmitted from the transceiver to a vehicle controller. A position of the at least one industrial truck within a previously known route to be driven is determined via the superordinate control unit. An upcoming driving situation is identified using the superordinate control unit and is based on the position of the at least one industrial truck and the driving job. A protective field is generated with a collision protection apparatus, wherein the protective field is monitored by the at least one industrial truck based on the upcoming driving situation even before the at least one industrial truck reaches the driving situation.

Abstract: A method and device for sensor data fusion for a vehicle as well as a computer program and a computer-readable storage medium are disclosed. At least one sensor device (S1) is associated with the vehicle (F), and in the method, fusion object data is provided representative of a fusion object (OF) detected in an environment of the vehicle (F); sensor object data is provided representative of a sensor object (OS) detected by the sensor device (S1) in the environment of the vehicle (F); indicator data is provided representative of an uncertainty in the determination of the sensor object data; reference point transformation candidates of the sensor object (OS) are determined depending on the indicator data; and an innovated fusion object is determined depending on the reference point transformation candidates.

Abstract: The vehicle control system includes a first controller configured to generate a target trajectory for the automated driving, and a second controller configured to execute vehicle travel control such that the vehicle follows the target trajectory. During the automated driving, the second controller controls a travel control amount which is a control amount of the vehicle travel control, acquire driving environment information, and execute preventive safety control for intervening in the travel control amount based on the driving environment information. The first controller includes a memory device in which information of an intervention suppression area is stored. When the vehicle travels in the intervention suppression area during the automated driving, the first controller outputs a suppression instruction for the preventive safety control to the second controller.

Abstract: Presented herein are techniques for updating detailed maps used to navigate an autonomous vehicle. The techniques include determining that a vehicle has come within a predetermined range of a road side unit, establishing a communication link with the vehicle, receiving, from the vehicle, data sufficient to identify a vehicle type of the vehicle, based on the vehicle type, selecting a map, stored by the road side unit, for the vehicle, sending a query to a neighbor road side unit seeking data to augment the map, in response to the query, receiving the data to augment the map from the neighbor road side unit, updating the map based on the data to augment the map to obtain an updated map, and sending at least a aspects of the updated map to the vehicle.

Abstract: A vehicular driving assistance system includes a plurality of sensors disposed at a vehicle and sensing respective regions exterior of the equipped vehicle. A plurality of microphones is disposed at the equipped vehicle and sense sounds emanating from exterior of the vehicle. An ECU, responsive to indication of an intended lane change of the equipped vehicle, and via processing of sensor data captured by at least one of the sensors, determines presence of another vehicle in an adjacent traffic lane. Responsive to determination of the presence of the other vehicle in the adjacent traffic lane, the ECU, via processing outputs of at least one microphone of the plurality of microphones, determines if the determined other vehicle is accelerating. Responsive to determination that the determined other vehicle is accelerating, the vehicular driving assistance system generates an alert to the driver of the equipped vehicle.

Abstract: An object-detection system for an automated vehicle includes an object-detector, a receiver, and a controller. The object-detector detects detectable-objects proximate to a host-vehicle. The receiver receives an indication of an object-presence from other-transmitters proximate to the host-vehicle. The controller is in communication with the object-detector and the receiver. The controller is configured to operate the host-vehicle to avoid interference with a hidden-object when the hidden-object is not detected by the object-detector and the object-presence is indicated by at least two instances of the other-transmitters.

Abstract: A collision avoidance assist apparatus calculates a lane marking recognition reliability level and execute an emergency steering control. The emergency steering control includes processes to determine a target steering torque to avoid a collision of a vehicle with an obstacle when determining that the vehicle has a high probability of colliding with the obstacle, a moving lane defined by the left and right lane markings is a straight lane, and the calculated lane marking recognition reliability level is equal to or higher than a first threshold reliability level, and apply a steering torque corresponding to the target steering torque to a steering mechanism. The collision avoidance assist apparatus stops executing the emergency steering control when the lane marking recognition reliability level becomes lower than a second threshold reliability level set to a value lower than the first threshold reliability level.

Abstract: A computer implemented method is provided for determining a collision free space in front of a host vehicle. A plurality of limiting points is detected via a detection system of the host vehicle, wherein each limiting point is located at a respective obstacle free distance with respect to the vehicle. A dynamic grid is formed in front of the host vehicle, wherein the dynamic grid is based on the course of a lane being determined in front of the host vehicle via the detection system of the host vehicle, and wherein the dynamic grid comprises a plurality of cells. An obstacle free subset of the cells is determined based on the plurality of limiting points, wherein the obstacle free subset of the cells defines the collision free space in front of a host vehicle.

Abstract: Systems and methods use cameras to provide autonomous navigation features. In one implementation, a method for navigating a user vehicle may include acquiring, using at least one image capture device, a plurality of images of an area in a vicinity of the user vehicle; determining from the plurality of images a first lane constraint on a first side of the user vehicle and a second lane constraint on a second side of the user vehicle opposite to the first side of the user vehicle; enabling the user vehicle to pass a target vehicle if the target vehicle is determined to be in a lane different from the lane in which the user vehicle is traveling; and causing the user vehicle to abort the pass before completion of the pass, if the target vehicle is determined to be entering the lane in which the user vehicle is traveling.

Abstract: Systems and methods use cameras to provide autonomous navigation features. In one implementation, a method for navigating a user vehicle may include acquiring, using at least one image capture device, a plurality of images of an area in a vicinity of the user vehicle; determining from the plurality of images a first lane constraint on a first side of the user vehicle and a second lane constraint on a second side of the user vehicle opposite to the first side of the user vehicle; enabling the user vehicle to pass a target vehicle if the target vehicle is determined to be in a lane different from the lane in which the user vehicle is traveling; and causing the user vehicle to abort the pass before completion of the pass, if the target vehicle is determined to be entering the lane in which the user vehicle is traveling.

Abstract: While operating a host vehicle in a lane, a target vehicle is detected entering the lane in front of the vehicle. A trajectory of the target vehicle is predicted based on sensor data. Upon determining that the target vehicle will pass through the lane based on the predicted trajectory, the host vehicle is operated based on determining a presence or an absence of a lead vehicle. Upon determining that the target vehicle will remain in the lane based on the predicted trajectory, the host vehicle is operated with the target vehicle as the lead vehicle.

Abstract: A target-orientated navigation system and related method for a vehicle having a generic navigation system includes one or more processors and a memory. The memory includes one or more modules that cause the processor to receive perception data, discretize the perception data into a plurality of lattices, generate a collision probability array having a plurality of cells that correspond to the plurality of lattices, determine which cells of the collision probability array satisfy a safety criteria, receive an artificial potential field array having a plurality of cells that correspond to the plurality of cells of the collision probability array, generate, an objective score array having a plurality of cells corresponding to the cells of the collision probability array, and direct a vehicle control system of the vehicle to guide the vehicle to a location representative of a cell in the objective score array that has a highest value.

Abstract: An estimated initial direction of movement of a newly-detected object is to be determined. The actual previous directions of movement and positions of previously-detected objects are determined and stored. When a newly-detected object is newly detected at a certain position, then the actual previous direction of movement of one of the previously-detected objects at that position is used as a basis to determine the estimated initial direction of movement of the newly-detected object at that position.

Abstract: The present invention relates to a collision distance estimation device and a driver assistance system using the same. The collision distance estimation device includes an image acquisition unit configured to acquire images of surroundings of a vehicle to generate image information, an image reading unit configured to detect and identify an object present around the vehicle from the image information to generate object recognition information, a travel detection unit configured to generate movement distance information on the basis of wheel sensing information, steering information, and the image information, and a collision distance calculation unit configured to calculate collision distance information on the basis of the object recognition information and the movement distance information.

Abstract: Systems and methods use cameras to provide autonomous navigation features. In one implementation, a method for navigating a user vehicle may include acquiring, using at least one image capture device, a plurality of images of an area in a vicinity of the user vehicle; determining from the plurality of images a first lane constraint on a first side of the user vehicle and a second lane constraint on a second side of the user vehicle opposite to the first side of the user vehicle; enabling the user vehicle to pass a target vehicle if the target vehicle is determined to be in a lane different from the lane in which the user vehicle is traveling; and causing the user vehicle to abort the pass before completion of the pass, if the target vehicle is determined to be entering the lane in which the user vehicle is traveling.

Abstract: Techniques are described for configuring a monitoring system to assist users during a detected emergency condition at a property. In some implementations, sensor data from one or more sensors that are located at the property are obtained by a monitoring system that is configured to monitor the property. A determination that there is an emergency condition at the property is made by the monitoring system based on the sensor data, determining. A location of a person inside the property is determined by the monitoring system based on the sensor data. A first path to the person and a second path to guide the person away from the emergency condition are determined by the monitoring system. The first path to the person and the second path to guide the person away from the emergency condition are navigated by a computing device of the monitoring system.

Abstract: This application is directed to on-vehicle behavior modeling of vehicles. A vehicle has one or more processors, memory, a plurality of sensors, and a vehicle control system. The vehicle collects training data via the plurality of sensors, and the training data include data for one or more vehicles during a collection period. The vehicle locally applies machine learning to train a vehicle driving behavior model using the collected training data. The vehicle driving behavior model is configured to predict a behavior of one or more vehicles. The vehicle subsequently collecting sensor data from the plurality of sensors and drives the vehicle by applying the vehicle driving behavior model to predict vehicle behavior based on the collected sensor data. The vehicle driving behavior model is configured to predict behavior of an ego vehicle and/or a distinct vehicle that appears near the ego vehicle.

Abstract: An emergency steering system for a vehicle includes a memory including instructions that, when executed by a processor, cause the processor to: receive information corresponding to an environment external to the vehicle; identify an obstacle in the environment external to the vehicle using the information; determine a distance between the vehicle and the obstacle; determine whether a collision is imminent; in response to determining that a collision is imminent, determine whether the vehicle can move within a lane of travel to avoid the collision; in response to determining that the vehicle can move within the lane of travel to avoid the collision, determine a trajectory of travel for the vehicle; generate a steering assist angle command based on the trajectory of travel; and control position of a steering mechanism of the vehicle using the steering assist angle command and a measured steering angle.

Abstract: A method for vehicle control. The method includes a step of reading in a camera signal, a step of executing a semantic segmentation, and a step of ascertaining a control signal. The camera signal represents an optically detected image of a roadway to be driven by a vehicle. In the step of executing, the semantic segmentation of the image represented by the camera signal is executed, to detect a free area ahead of the vehicle from the image as a drivable road section. In addition, a roadway signal representing the detected drivable road section is provided. In the step of ascertaining, the control signal for activating at least one vehicle component is ascertained, using the roadway signal.

Abstract: A vehicle driving behavior monitoring and warning system that includes a host vehicle having a communication device that receives operating information of remote vehicles that are located within a predetermined zone of interest, a warning device and an electronic controller. The electronic controller is connected to the communication device and the warning device. The electronic controller evaluates operating information received by the communication device and determine whether or not one of the remote vehicles is operating with questionable driving behavior and determines whether or not the remote vehicle poses a potential threat to the host vehicle. In response to determining that the remote vehicle is operating with questionable driving behavior and poses a potential threat to the host vehicle, the electronic controller operates the warning device warning the operator of the host vehicle of the remote vehicle.

Abstract: Systems and methods are provided for navigating an autonomous vehicle. In one implementation, a system for navigating a vehicle includes at least one processing device programmed to receive, from an image capture device, a plurality of images associated with an environment of the vehicle, analyze at least one of the plurality of images to identify a navigable region in the environment of the vehicle, identify, based on the at least one of the plurality of images, at least one barrier associated with an edge of the navigable region, and determine a type of the at least one barrier. The at least one processing device is also programmed to determine a navigational path of the vehicle based on the determined type of the at least one barrier, and cause the vehicle to travel on at least a portion of the determined navigational path.

Abstract: In one embodiment, a processor of a vehicle detects a difference between a physical characteristic of the vehicle predicted by a first machine learning-based model and a physical characteristic of the vehicle indicated by telemetry data generated by a sub-system of the vehicle. The processor forms a packet payload of an update packet indicative of the detected difference, based in part on a relevancy of the physical characteristic to the first machine learning-based model. The processor applies a synchronization strategy to the update packet, to synchronize the update packet with a second machine learning-based model executed by a receiver. The processor sends the update packet to the receiver via a network, to update the second machine learning-based model.

Abstract: An apparatus, method and computer program is described comprising the following: receiving telemetry and/or motion vector data and distance data from a distance sensor of the drone or unmanned aerial vehicle (32); determining a segment of interest dependent on said telemetry data and/or motion vector data; processing said distance data to determine whether an obstacle falls within said segment of interest (34); receiving imaging data; and providing imaging data analysis in the event that an obstacle is determined to fall within said segment of interest (36).

Abstract: An autonomous vehicle is described, wherein the autonomous vehicle is configured to estimate a change in direction of a vehicle that is on a roadway and is proximate to the autonomous vehicle. The autonomous vehicle has a mechanical system, one or more sensors that generate one or more sensor signals, and a computing system in communication with the mechanical system and the one or more sensors. The autonomous vehicle is configured to detect an imminent lane change by another vehicle based on at least one of a computed angle between a wheel of the other vehicle and a longitudinal direction of travel of the other vehicle, a degree of misalignment between the wheel of the other vehicle and a body of the other vehicle, and/or an eccentricity of the wheel of the other vehicle. The mechanical system of the autonomous vehicle is controlled by the computing system based upon the detected imminent lane change.

Abstract: A method for risk-aware game-theoretic trajectory planning is described. The method includes modeling an ego vehicle and at least one other vehicle as risk-aware agents in a game-theoretic driving environment. The method also includes ranking upcoming planned trajectories according to a risk-aware cost function of the ego vehicle and a risk-sensitivity of the other vehicle associated with each of the upcoming planned trajectories. The method further includes selecting a vehicle trajectory according to the ranking of the upcoming planned trajectories based on the risk-aware cost function and the risk-sensitivity of the other vehicle associated with each of the upcoming planned trajectories to reach a target destination according to a mission plan.

Abstract: A driving assistance device includes: a line-of-sight direction detection unit that detects a direction of a line of sight of a driver of a moving body; an obstacle detection unit that detects a position of an obstacle in environs of the moving body; an assessment criteria determination unit that determines assessment criteria of a look at the obstacle by the driver based on at least one of time, location, weather, a state of the moving body, and a state of the driver; and a warning processing unit that obtains an assessment result by applying, to the assessment criteria, a score computed based on the direction of the line of sight of the driver and the position of the obstacle, the warning processing unit determining at least one of whether or not a warning needs to be issued to the driver and a level of the warning, based on the assessment result.

Abstract: A driver assistance system that notifies the driver of the braking information of the preceding vehicle or improves the sensitivity of the emergency braking system if the brake lamp of the preceding vehicle is failed includes: a first sensor mounted in a vehicle, having a front field of view of the vehicle, and configured to acquire a front image data; a second sensor selected from a group consisting of a radar sensor and a lidar sensor, mounted in the vehicle, having a front field of sensing of the vehicle, and configured to acquire a front detection data; and a controller including a processor configured to process the front image data and the front detection data, and the controller is configured to: detect a velocity of the preceding vehicle travelling in front of the vehicle and a brake lamp of the preceding vehicle in response to processing the front image data and the front detection data; and determine whether the brake lamp of the preceding vehicle is failed based on the velocity of the preceding veh

Abstract: A vehicle driving assist apparatus includes a first unit to set a degree of acceleration suppression to suppress acceleration of a vehicle, a controller to suppress target acceleration of the own vehicle based on the degree of acceleration suppression, a storage to store road map information, an estimator to estimate a vehicle position, a detector to map-match the estimated vehicle position to the road map information and detect whether there is a crossing road ahead of the vehicle, a second setting unit to set, when the detector detects the crossing road, a traveling-prohibited region on an opposite side of the vehicle on the road map information, and a calculator to calculate a reaching distance from the vehicle to the region. The degree of acceleration suppression is set to a higher value as the reaching distance becomes shorter.

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.