Abstract: A vehicle includes a traveling information acquiring device configured to recognize a first vehicle that travels in the same lane as the vehicle and in front of the vehicle, recognize a second vehicle that travels in the same lane as the vehicle and travels in front of the first vehicle and acquire traveling information of the first vehicle and the second vehicle; and a control device configured to control the behavior of the vehicle acceleration or deceleration based on a vehicle speed difference between a vehicle speed of the first vehicle and the vehicle speed of the second vehicle when the second vehicle is recognized during the execution of the follow-up control that controls the vehicle speed of the vehicle and adjusts the distance between the vehicle and the first vehicle.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for agent trajectory prediction using vectorized inputs.

Abstract: Provided are a method, a server, and a computer program for creating a road network map to design a driving plan for an autonomous driving vehicle. A method of creating a road network map to design a driving plan for an autonomous driving vehicle is performed by a computing device and includes: generating road network data for an area; generating lattice road network data for a short-term driving plan for an autonomous driving vehicle using the generated road network data; and generating a crossable dipole graph for a long-term driving plan for the autonomous driving vehicle using the generated lattice road network data.

Abstract: Vehicle systems, computer-implemented methods, and computer program products to enhance the situational competency and/or the safe operation of a vehicle by automatically controlling the vehicle in response to executing measurable attribute data analysis that includes a comparison of the relative height of a detected road infrastructure element with a predetermined threshold height value.

Abstract: Techniques for determining behavior profiles and unique identities for objects observed in an environment surrounding an autonomous vehicle are described. The behavior profiles may be generated and associated with unique identifiers that are stored and used by a fleet of vehicles for planning and navigating in traffic environments. The behavior profiles may be used to control operation of the vehicle and increase safety of the vehicle by identifying potentially risky or erratic objects and navigating through the environment accordingly. The behavior profiles may be stored at a central database and propagated across a fleet to increase observations used to build profiles and thereby increase profile confidence.

Abstract: A system for generating and presenting an explanation to a user includes an input module configured to receive sensor data and input the sensor data to a control system of an automated system, the control system configured to control operation of the automated system based on the sensor data and according to a gray box decision making algorithm. The system also includes an explanation module configured to generate an explanation of a decision made by the control system and a corresponding behavior of the automated system, the explanation generated based on at least one of: a request by the user, and a user model, and a display module configured to present the generated explanation to the user.

Abstract: A target vehicle recognition apparatus detects a stopped vehicle ahead of the host vehicle, detects a reference boundary line position where at least one of two boundary lines forming a travel lane of the host vehicle intersects a reference axis extending from a lower end of the stopped vehicle in an image horizontal direction on a captured image, recognizes the stopped vehicle as a target vehicle of steering control when the reference boundary line position between a vehicle left end position of the stopped vehicle and a vehicle right end position of the stopped vehicle is present, and does not recognize the stopped vehicle as a target vehicle of steering control when the reference boundary line position between the vehicle left end position of the stopped vehicle and the vehicle right end position of the stopped vehicle is not present.

Abstract: A system for dynamically managing individual suspension settings for a vehicle based on a determined suspension mode is provided. Based on the user input and obtained sensor input, the system can then determine a suspension mode for a plurality of individually controllable components by specifying values or commands for each controllable component. A first mode may correspond to a lowering of the plurality of controllable. A second mode may correspond to lowering two controllable components corresponding to the rear wheels of the vehicle and raising two controllable components corresponding to front wheels of the vehicle. A third mode may correspond to a lowering of the plurality of controllable components to effectively drop the height of the vehicle to a threshold point. The system may further implement various validation processes that can validate the determined suspension mode and make further adjustment to individual controllable portions based on load or ground measurements.

Abstract: A method for performing at least one perception task associated with autonomous vehicle control includes receiving a first dataset and identifying a first object category of objects associated with the plurality of images, the first object category including a plurality of object types. The method also includes identifying a current statistical distribution of a first object type of the plurality of object types and determining a first distribution difference between the current statistical distribution of the first object type and a standard statistical distribution associated with the first object category. The method also includes, in response to a determination that the first distribution difference is greater than a threshold, generating first object type data corresponding to the first object type, configuring at least one attribute of the first object type data, and generating a second dataset by augmenting the first dataset using the first object type data.

Abstract: Techniques for protecting electronic vehicles control systems from unauthorized intrusion work with at least one electronic module of the vehicle and a protection device connected via electrical conductors to the interface communication line. The protection device includes a control unit for monitoring and control of vehicle parameters, a passive scanning of interface communication lines unit, a spectral analysis of interface communication lines unit, a unit for detection and suppression of malicious commands, and a unit for detecting and jamming in a given frequency range an unauthorized receiver/transmitter. The units for passive scanning of interface communication lines, spectral analysis, and detection and suppression of malicious commands are connected to the interface communication line.

Abstract: A safety device for a vehicle including a memory configured to store instructions; one or more processors coupled to the memory to execute the instructions stored in the memory, wherein the instructions implement a safety driving model for the vehicle to determine a safety driving state for the vehicle, wherein determining includes obtaining data for one or more objects in a vehicle environment of the vehicle, wherein the data comprises motion data associated with at least one object of the one or more objects; determining a predicted motion trajectory for at least one object of the one or more objects; determining whether a risk indicating a risk of a collision for the vehicle and the at least one or more objects exceeds a predefined risk threshold; and generating an information that the risk exceeds the predefined risk threshold to be considered in determining the safety driving state for the vehicle.

Abstract: A pedestrian protection system includes a plurality of autonomous driving vehicles and a server configured to be able to communicate with each of the autonomous driving vehicles. The server is configured to select at least one vehicle to be moved to the location of a pedestrian from among the autonomous driving vehicles as a pedestrian protection vehicle when a particular situation occurrence notification is received and is configured to send an instruction notification to the pedestrian protection vehicle. The particular situation occurrence notification indicates that the pedestrian is placed in a particular situation. The instruction notification instructs the pedestrian protection vehicle to move to the location of the pedestrian for protecting the pedestrian. Each of the autonomous driving vehicles is configured to move to the location of the pedestrian for protecting the pedestrian when the instruction notification is received.

Abstract: A work vehicle includes a traveling vehicle body, a coupler capable of coupling a working device including working implements to the traveling vehicle body, an automatic operation controller configured or programmed to automatically operate the traveling vehicle body based on a planned traveling route, and a work setting controller configured or programmed to set a work start position and a work end position for the working device at different positions based on the working implements.

Abstract: A passenger protection method includes obtaining in-vehicle passenger information and in-vehicle environment information; determining an abnormal state type and an abnormality degree based on the in-vehicle passenger information and the in-vehicle environment information; and determining, based on the abnormal state type and the abnormality degree, an emergency measure for reducing the abnormality degree.

Abstract: A system for dynamically managing individual suspension settings for a vehicle based on a determined suspension mode is provided. Based on the user input and obtained sensor input, the system can then determine a suspension mode for a plurality of individually controllable components by specifying values or commands for each controllable component. A first mode may correspond to a lowering of the plurality of controllable. A second mode may correspond to lowering two controllable components corresponding to the rear wheels of the vehicle and raising two controllable components corresponding to front wheels of the vehicle. A third mode may correspond to a lowering of the plurality of controllable components to effectively drop the height of the vehicle to a threshold point. The system may further implement various validation processes that can validate the determined suspension mode and make further adjustment to individual controllable portions based on load or ground measurements.

Abstract: A platooning control system includes a platoon controller that generates environmental maps used for platooning of vehicles, and a travel controller that controls travel of a following vehicle following a leading vehicle. The platoon controller generates the environmental maps each representing the position of an object around the vehicles, and delivers the maps to the following vehicle. The travel controller transmits object information indicating the position of an object detected from environmental data outputted by an environmental sensor mounted on the following vehicle to the platoon controller, executes update so that the position of the object represented in the latest environmental map is changed to the position of the object at the time when the following vehicle reaches the position of the leading vehicle represented in the latest environmental map, and controls travel of the following.

Abstract: The present application provides a method and device for merging a vehicle from a branch road into a main road, an electronic device, and a storage medium, which relates to a technical field of unmanned driving. The method for merging the vehicle from the branch road into the main road includes: acquiring vehicle information of the vehicle to be merged from the branch road into the main road; acquiring traffic flow information of an outer lane of the main road within a preset range of a junction; controlling the vehicle to be merged into the main road to merge into the main road according to the preset rules based on the traffic flow information of the outer lane of the main road and the vehicle information of the vehicle to be merged into the main road.

Abstract: A functionality utilizing a centrally controlled strategy for continuous communication to specific autonomous vehicles, or drones, that are designed for extreme conditions and assigned specific missions with the ability to be replaced during the mission. This functionality is an improvement on existing swarm and leader-follower tactics as it retains control of the drones at a central command center, allowing the drones to both receive individual commands from the hub but also operate independently of it with direct pilot control. This direct communication allows for real time process of ordered substitution to replace any drone during the mission.

Abstract: By the vehicle control method, in a vehicle provided with wheel, a sensor that acquires rotation speed of the wheel, and a sound generation device that generates sound as the sound generation device is driven, the angular acceleration of wheel is obtained from the rotation speed acquired by a sensor, and a sound generation device is controlled such that the generated sound becomes louder when conditions are met. Cases in which the angular acceleration is high are included in the conditions.

Abstract: A vehicle control system including a spatial monitoring system includes on-vehicle cameras that capture images, from which are recovered a plurality of three-dimensional points. A left ground plane normal vector is determined for a left image, a center ground plane normal vector is determined for a front image, and a right ground plane normal vector is determined for a right image. A first angle difference between the left ground plane normal vector and the center ground plane normal vector is determined, and a second angle difference between the right ground plane normal vector and the center ground plane normal vector is determined. An uneven ground surface is determined based upon one of the first angle difference or the second angle difference, and an alignment compensation factor for the left camera or the right camera is determined. A bird's eye view image is determined based upon the alignment compensation factor.