Abstract: Aspects relate to methods and systems for parking a vehicle. An exemplary system includes a first plurality of sensors located on the vehicle and configured to detect first sensor data as a function of objects over a first height range, a second plurality of sensors located on the vehicle and configured to detect second sensor data as a function of objects over a second height range at least partially greater than the first height range, and a computing device configured to receive the first sensor data from the first plurality of sensors and the second sensor data from the second plurality of sensors, and determine the space proximal the vehicle is suitable for parking the vehicle as a function of the first sensor data, the second sensor data, and a height of the vehicle.

Abstract: A parking assistance apparatus includes at least one camera sensor installed in a vehicle, a control unit configured to analyze an image obtained through the camera sensor to recognize a space and object in a parking lot by matching a detailed parking lot map to an object, search for an available parking space by calculating a parking region on the basis of recognized space and object information, and generate a path to the available parking space searched for, or perform autonomous parking until reaching the available parking space, and a storage unit configured to store the detailed parking lot map for recognizing the space and object.

Abstract: Provided is an intelligent safe vehicle speed measurement method and an system capable of considering a state of a road surface, including: a laser scanning unit configured to obtain road surface textures and simulate contact under different vehicle loads and tire patterns; a wireless communication unit configured to obtain the model, load and tire information of incoming vehicles, offer a best-matching braking distance by search through database; a skid resistance prediction unit configured to obtain environmental parameters to correct the obtained best-matching braking distance, and offer a safe speed for incoming vehicles; and a warning reminder unit configured to broadcast the safe running speed to incoming vehicles. This system communicates between the vehicle and road, obtains the information from incoming vehicles in real time, and broadcasts the safe speed to incoming vehicles, ensuring the safety of the incoming vehicle during running.

Abstract: The present application comprises a system for controlling a plurality of autonomous vehicles on a mine site, the system comprising: a centralized platform configured to store an inventory list of vehicles travelling on the mine site and comprising a first communication interface configured to communicate missions to the vehicles; a plurality of autonomous vehicles, the autonomous vehicles comprising: a first communication interface configured to wirelessly communicate with the centralized platform for receiving a predetermined mission, a trajectory control system configured to autonomously control the autonomous vehicle according to the predetermined mission; and at least one portable device, the portable device comprising a second communication interface configured to wirelessly communicate with a second communication interface of the plurality of vehicles from the mine site.

Abstract: This document describes techniques, apparatuses, and systems for a grid-based road model with multiple layers. An example road-perception system generates a roadway grid representation that includes multiple cells. The road-perception system uses data from multiple information sources to generate a road model that includes multiple layers. Each layer represents a roadway attribute of each cell in the grid and includes one or more layer hypotheses. In this way, the described techniques and systems can provide an accurate and reliable road model and quantify uncertainty therein.

Abstract: Distributed data sampling, including: receiving a sampling target; generating, based on one or more sensors, sampled data; determining, based on the sampling target, a value for the sampled data; and determining, based on the value for the sampled data, whether to provide the sampled data to a remotely disposed computing device.

Abstract: A controller of a machine determines jointly a sequence of control inputs defining a state trajectory of the machine and a desired knowledge of the environment by solving a multivariable constrained optimization of a model of dynamics of the machine relating the state trajectory with the sequence of control inputs subject to a constraint on admissible values of the states and the control inputs defined based on the desired knowledge of the surrounding environment represented by the state of the environment and the uncertainty of the state of the environment determined from the measurements of the environment. In such a manner, the controller performs joint but imbalance optimization of the control inputs and the sensing instructions to the sensor for learning the environment.

Abstract: A damping control system for a vehicle having a suspension located between a plurality of ground engaging members and a vehicle frame are disclosed. The vehicle including at least one adjustable shock absorber having an adjustable damping characteristic.

Abstract: Systems and methods for detecting degraded navigation sensors are based on a policy derived from a Partially Observable Markoff Decision Process (POMDP). Navigation parameters derived from the navigation sensors are provided to individual Kalman filters. A covariance of each of the filters is indicative of a probability of degradation of a sensor from which the navigation parameter is derived. Outputs of the Kalman filters are provided to a master filter. The master filter is compared to a criterion to determine whether there are indicia of a degraded sensor. If such an indicia are present, the Policy is consulted to determine which of the sensors are degraded. Consideration of degraded sensors when navigating a vehicle is inhibited.

Abstract: An electronic apparatus for providing a traversability map of a robot and a controlling method thereof are provided. The electronic apparatus includes a transceiver, a memory configured to store feature information of each of a plurality of robots, and at least one processor configured to receive sensing data obtained by sensing vicinity by at least one external device from the external device from the at least one external device, through the transceiver, generate at least one map with respect to a space where the at least one external device is positioned based on the received sensing data, generate a traversability map for traversal of a robot based on feature information of at least one robot among the plurality of robots and the generated at least one map, and control the transceiver to transmit the traversability map to the robot.

Abstract: A steering control device according to the present invention is configured to obtain information on a parking position of a vehicle obtained by an external world recognition unit, and to output, based on the obtained information on the parking position, an instruction for moving a rear portion of the vehicle to a set position in a parking width direction to a rear-wheel steering device configured to control a steered angle of rear wheels of the vehicle. With this configuration, even when a timing or an angle for operating a steering wheel by a driver is not appropriate, or even when a steered angle of front wheels is limited, parking of the vehicle at the predetermined position in the parking width direction is facilitated.

Abstract: System, methods, and other embodiments described herein relate to improving the synchronizing of systems in a vehicle without relying on external controls or hardware. In one embodiment, a method includes detecting a stop of a vehicle according to data acquired from two or more sensors. The method also includes identifying motion from the stop according to the data and corresponding timestamps from the two or more sensors, wherein the data and the corresponding timestamps are internal to the two or more sensors. The method also includes synchronizing the two or more sensors according to the corresponding timestamps. The method also includes controlling the motion of the vehicle using the two or more sensors.

Abstract: Systems and methods for navigating a host vehicle are disclosed. In one implementation, a system includes a processor configured to receive a first image acquired by a first camera and a second image acquired by a second camera onboard the host vehicle; identify a first representation of an object in the first image and a second representation of the object in the second image; input to a first trained model at least a portion of the first image; input to a second trained model at least a portion of the second image; receive the first signature encoding determined by the first trained model and the second signature encoding determined by the second trained model; input to a third trained model the first signature encoding and the second signature encoding; and receive an indicator of a location of the object determined by the third trained model.

Abstract: A system uses an obstacle map to determine an avoidance map that indicates one or more constraint regions that are present in a physical space. The obstacle map is processed using a smoothing function and the smoothed map processed with a medial axis transform function to generate a MAT skeleton. The skeleton is pruned to remove spurs and then segmented based on MAT values that are representative of distances in the physical space between the skeleton and an obstacle. The avoidance map is determined by associating constraint regions with the segments. Constraint regions may indicate areas in the physical space that are open for the autonomous mobile device (AMD) to stop, narrow areas for which stopping should be avoided, and closed areas within which the AMD is not to stop during ordinary operation.

Abstract: Systems and methods for predictively detecting vehicle failure based on diagnostic trouble codes are provided. In one example, a method is provided, comprising determining a probability of failure of a vehicle based on one or more diagnostic trouble codes (DTCs); and indicating to an operator of the vehicle that failure is likely in response to the probability exceeding a threshold.

Abstract: A vehicle or a mobile device within or near the vehicle can have multiple sensors to sense biometric features of a user or driver, and electronic circuitry (such as a computing system) can classify the user or driver according to the sensed biometric features. Also, non-biometric factors of the user or driver or of the mobile device of the user or driver can be used to classify the user or driver, e.g., MAC address, RFID, username and password, PIN, etc. Also, factors from interaction with a user interface of the vehicle or the mobile device can be used to classify the user or driver. Such features and factors can be used alone or in combination for the classification, and the classification can use AI (such as an ANN). The vehicle or the mobile device can then selectively enable or disable features of the vehicle based on the classification.

Abstract: A driving assistance device includes a lane change detection unit, a lane identification unit, a first space determination unit, an operation control unit. The lane identification unit identifies an original lane and a destination lane by using a detection result obtained by a boundary detection unit that detects a first boundary and a second boundary. The first boundary is a boundary between the original lane and the destination lane, and the second boundary is a boundary that defines the original lane and is located on a side opposite to the first boundary. When it is detected that the own vehicle is scheduled to perform a lane change and it is determined that the passable space is present, the operation control unit causes the own vehicle to perform a lateral movement operation before the lane change is performed. The lateral movement operation causes the own vehicle to approach the destination lane.

Abstract: The autonomous driving system includes an internal vehicle camera, a vehicle detection device, and a processor configured to detect an angle of a facial direction or a line of sight of the driver, judge whether the driver has checked safety of the surroundings of the vehicle based on the angle, and control autonomous driving of the vehicle. The processor is configured to start a lane change of the vehicle when it is judged that the driver has checked the safety of the surroundings of the vehicle. The processor is configured to judge that the driver has checked the safety when a first condition has been satisfied if another vehicle has not been detected in a destination lane, and judge that the driver has checked the safety when a second condition more severe than the first condition has been satisfied if another vehicle has been detected in the destination lane.

Abstract: A road abnormality detection apparatus includes: a memory; and a processor having hardware, wherein the processor is configured to: receive, from a traveling vehicle, a road image indicating an image of a surface of a road or a periphery of the road and image capturing position information indicating a position where the road image is captured; recognize a road facility included in the road image and a position of the road facility based on the road image and the image capturing position information; determine whether or not abnormality exists in the road facility by comparing the road facility included in the road image and correctness information that is prepared in advance; and accumulate, in the memory, facility position information indicating the position of the road facility that the abnormality exists in when it is determined that the abnormality exists in the road facility.

Abstract: Synchronization of multiple vehicles in an independent cart system to reduce spacing and increase throughput designates one of the movers as a leader and at least one additional mover as a follower, defining a chain of vehicles. A motion command for the chain is provided to a controller for the leader, and the controller generates a motion profile. The controller passes this motion profile to a controller for each of the follower movers. If the follower is unable to maintain the motion profile for the leader, the controller for the follower generates a message to the controller for the leader indicating a modification to the motion profile is required. The controller for the leader modifies the motion profile and forwards the modified motion profile to controllers for each follower. If all movers are following the modified profile, the controller for the leader may return to the original motion profile.