The disclosure provides for systems and methods for communicating messages from one vehicle to another vehicle. An input device, such as a cell phone, can be configured to generate and transmit a signal that corresponds with a message to an output device for display of messages. The messages can be displayed in a rearward direction, allowing drivers to communicate with vehicles located behind them on a roadway.

A driving assistance apparatus includes an outside recognition device, a locator unit, and a driving control unit. The outside recognition device is configured to acquire traffic environment information around the vehicle. The locator unit is configured to store road map information and detect a position of the vehicle based on a positioning signal. The driving control unit is configured to control the vehicle based on forward traffic environment information acquired by the outside recognition device. The driving control unit is configured to execute a wrong-way driving detection process and a restricted traffic zone determination process to determine whether the vehicle is performing wrong-way driving in an oncoming lane. The wrong-way driving detection process involves detecting wrong-way driving of the vehicle from the traffic environment information, and the restricted traffic zone determination process involves detecting a restricted traffic zone in a driving lane of the vehicle from the traffic environment information.

A vehicle control apparatus determines a travelling region in which the vehicle is travelling among a plurality of regions into which an area is divided by a predetermined boundary line. When an obtained position which is determined based on a positioning signal from a positioning satellite is not included in a boundary zone, the apparatus determines that the travelling region is a region in which the obtained position is included. The boundary zone is a belt-like zone including the boundary line. Meanwhile, when the obtained position is not included in the boundary zone, the apparatus determines the travelling region based on a piece of information included in an image of an area in front of the vehicle. Each piece of the information is associated with one of the regions having a part overlapping the boundary zone.

Methods, systems, and products for resolving level ambiguity for radar systems of autonomous vehicles may include detecting a plurality of objects with a radar system. Each first detected object may be associated with an existing tracked object based on a first position thereof. First tracked object data based on a first height determined for each first detected object may be stored. The first height may be based on the position of the detected object, the existing tracked object, and a tile map. Second tracked object data based on a second height determined for each second detected object not associated with the existing tracked object(s) may be stored. The second height may be based on a position of each second detected object, a vector map, and the tile map. A command to cause the autonomous vehicle to perform at least one autonomous driving operation may be issued.

Among other things, techniques are described for spatially and temporally consistent ground modelling with information fusion. A vehicle location and orientation is obtained and an instantaneous ground height estimation is obtained for anchor cells of a grid map of the vehicle based on the obtained vehicle location and orientation. A pseudo ground height associated with non-anchor cells of the grid map is computed. A Bayesian filtering framework is used to generate a final ground height estimate for the anchor cells and the non-anchor cells based on the instantaneous ground height estimation for the anchor cells, the pseudo ground height associated with non-anchor cells, an estimated ground height from a previous timestamp, or any combinations thereof. The vehicle operates according to the final ground height estimate.

A navigation system includes: a control circuit configured to: generate a video clip by parsing an interval of a sensor data stream for a region of travel; analyze the video clip submitted to a deep learning model, already trained, including identifying a traffic flow estimate; access a position coordinate for calculating a distance to intersection; generate a traffic flow state by fusing a corrected speed, the traffic flow estimate, and the distance to intersection; merge a vehicle maneuvering instruction into the traffic flow state for maneuvering through the region of travel; and a communication circuit, coupled to the control circuit, configured to: communicate the traffic flow state for displaying on a device.

A method and an assistance device assist automated driving operation of a motor vehicle. Surroundings raw data recorded by way of a surroundings sensor system of the motor vehicle are processed by the assistance device in order to generate semantic surroundings data. This is accomplished by carrying out semantic object recognition. Further, a comparison of predefined semantically annotated map data against the semantic surroundings data is performed. This involves static objects indicated in the map data being identified in the semantic surroundings data as far as possible. Discrepancies detected during the process are used to recognize perception errors of the assistance device. A recognized perception error prompts a predefined safety measure to be carried out.

The present disclosure relates to an information processing apparatus, an information processing method, and a program that allow for appropriately pulling over to a safe road shoulder when an emergency occurs during automated driving. On the basis of distance information from a depth sensor or the like, a travelable region available for a vehicle to travel is set like an occupancy map, and image attribute information is generated from an image by semantic segmentation. On the basis of the image attribute information, an evacuation space is set in the travelable region in accordance with the situation of the road surface of the travelable region, and thus an evacuation space map is created. The present disclosure can be applied to a mobile object.

Included are an identification data input unit (11) to which identification data for identifying an occupant of a vehicle is input, a preference data storage unit (12) configured to store preference data regarding a preference of the occupant in association with the identification data, an object acquisition unit (13) configured to acquire object data of objects existing around an occupant on board the vehicle, a determination unit (15) configured to determine whether or not an object included in the object data is visually or audibly recognizable by the occupant on board the vehicle, and a notification data generator (16) configured to generate notification data for the occupant on board the vehicle based on the preference data of the occupant and the object for which the determination unit determines that it is recognizable by the occupant. The preference data of the occupant is stored in the preference data storage unit and associated with the identification data.

One or more processors may be configured to determine one or more prospective routes of an ego vehicle being at least partially controlled by a human driver; receive first sensor data, representing one or more attributes of a second vehicle; determine a danger probability of the one or more prospective routes of the first vehicle using the at least the one or more attributes of the second vehicle from the first sensor data; and if each of the one or more prospective routes of the first vehicle has a danger probability outside of a predetermined range, send a signal representing a safety intervention. Whenever a safety intervention signal is sent, the one or more processors may be configured to increment or decrement a counter.