A system for an attention-based perception includes a camera device configured to provide an image of an operating environment of a vehicle. The system further includes a computerized device monitoring the image, analyzing sensor data to identify a feature in the image as corresponding to an object in the operating environment and assign a score for the feature based upon an identification, a location, or a behavior of the object. The computerized device is further operable to define candidate regions of interest upon the image, correlate the score for the feature to the candidate regions of interest to accrue a total region score, select some of the candidate regions for analysis based upon the total region scores, and analyze the portion of the candidate regions to generate a path of travel output. The system further includes a device controlling the vehicle based upon the output.

A device for identifying a signaling unit on a road on which a vehicle is traveling is described. The device is configured to determine an arrangement of one or more signal signs of the signaling unit on the basis of environmental data of one or more environmental sensors of the vehicle. The device is further configured to assign the one or more signal signs to one or more corresponding grid cells of a signal sign grid based on assignment logic.

A driving support system includes: an information acquisition unit configured to acquire traveling characteristic information on a vehicle; a storage unit in which a dynamic map is stored, the dynamic map being a map in which static base map information, dynamic environmental information, and the traveling characteristic information acquired by the information acquisition unit are associated with each other; a collision determination unit configured to determine whether or not there is a possibility that the vehicle has a collision, based on the dynamic map stored in the storage unit; and a control unit configured to, in a case where the collision determination unit determines that there is a possibility that the vehicle has a collision, control the vehicle such that the vehicle avoids the collision.

A vehicle control system is applied to a vehicle equipped with a magnetic sensor configured to detect a magnetic marker on a road. The vehicle control system executes a self-driving control by which self-driving of the vehicle is controlled. The vehicle control system executes a retreat traveling control using the magnetic marker in response to the occurrence of an abnormality in at least part of components and functions necessary for the self-driving control. The magnetic marker provides guidance information by which the vehicle is guided to a safe area. In the retreat traveling control using the magnetic marker, the vehicle control system acquires the guidance information from the magnetic marker detected by the magnetic sensor and causes the vehicle to travel toward the safe area and stop at the safe area based on the guidance information thus acquired.

A vehicle control method includes: controlling a vehicle based on a lane position obtained from map information; detecting a lane boundary around the vehicle using a sensor mounted on the vehicle; and determining that the map information deviates from an actual state when a predetermined condition is met. The predetermined condition is met when a state in which a first distance is equal to or less than a first threshold continues for a first time or more or when a state in which a second distance is equal to or more than a second threshold continues for a second time or more. The first distance is a distance between a travel position of the vehicle and the detected lane boundary. The second distance is a distance between a lane boundary obtained from the map information and the detected lane boundary.

A computer-implemented method of refining a high definition (HD) map of a parking lot for autonomous vehicle parking (AVP) is disclosed. The method including: a vehicle navigating in the parking lot using the HD map; the vehicle using one or more sensors to scan for objects in the parking lot; the vehicle augmenting the HD map using a simultaneous localization & mapping SLAM method; adding objects detected by the one or more sensors to the HD map; and contributing towards improving a learning score of the HD map.

An embodiment system for updating high-definition maps for autonomous driving includes a vehicle electronic device configured to transmit determination result data of whether there is consistency with a high-definition map or analysis result data of a difference from the high-definition map, with respect to positioning data for a current location provided from a plurality of sensors according to a presence or an absence of policy information for a driving section and a server configured to provide the policy information and high-definition map data for the driving section to the vehicle electronic device, to determine whether an update is required based on the data received from the vehicle electronic device, and to update the high-definition map data based on the received positioning data.

Systems and methods for situational behavior of an autonomous vehicle are disclosed. In one aspect, an autonomous vehicle includes at least one perception sensor configured to generate perception data indicative of at least one other vehicle on a roadway, a non-transitory computer readable medium, and a processor. The processor is configured to determine that the other vehicle is violating one or more rules of the roadway based on the perception data, tag the other vehicle as a non-compliant driver, and modify control of the autonomous vehicle in response to tagging the other vehicle as a non-compliant driver.

A computer implemented method for scenario generation for autonomous vehicle navigation that can include defining a cellular automaton layer that defines a road network level behavior with at least one rule directed to pathways by vehicles on a passageway for travel. The method may further include defining an active matter layer that defines a vehicle level behavior with at least one rule directed to movement of the vehicles on an ideal route for the pathways; and defining a driver agent layer that defines driving nature with at least one rule that impacts changes in the vehicle level behavior dependent upon a characterization of driver behavior. The method may further include combining outputs from the different layer to provide scenario generations for autonomous vehicle navigation. The combining of the outputs can utilize a pseudo random value to determine at an order in the execution and duration of execution for the layers.

A method, apparatus, and computer program product are provided for identifying the reliability of objects within a mapped region for localization and facilitating autonomous control of a vehicle. Methods may include: receiving an indication of an event having event data; assigning at least one object at a location of the event an impact score based on an estimated impact of the event; and providing an indication of a reduction in autonomous vehicle capability in response to the impact score failing to satisfy a predetermined value. The impact score may include a probability that the corresponding object is reliable for localization or autonomous vehicle control. Methods may include providing the indication of a reduction in autonomous vehicle capability to at least one device associated with a vehicle in response to the at least one device associated with the vehicle having a travel path including the at least one road link.