A vehicle computing system may implement techniques to improve collision prediction and avoidance between a vehicle and objects in an environment. A vehicle computing system of the vehicle generates a relevance polygon associated with a planned path of the vehicle based at least in part on a speed associated with the vehicle traveling through the environment. The vehicle computing system identifies objects in the environment and determines whether the objects are located within a boundary of the relevance polygon. Based on a determination that an object is within the boundary, the vehicle computing system determines that the object is relevant to the vehicle and includes data associated therewith in vehicle control planning considerations.

Systems and methods for authenticating autonomous vehicle travel networks are provided. A system can obtain map data descriptive of a number of segment attributes for a number of travel way segments within a travel way network. The system can obtain operational domain parameters for the travel way segments and generate an operational domain including a number of operational travel way segments with segment attributes that achieve the operational domain parameters. The system can compare the operational domain to approval criteria associated with a service entity to verify that the operational travel way segments of the operational domain comply with service entity policies. The system can provide a verified operational domain to an autonomous vehicle for use in traversing the travel network. An operational domain that does not meet the approval criteria can be modified to comply with the approval criteria before being provided to an autonomous vehicle.

A local computing device receives lidar data and radar data from one or more road side units (RSUs). The local computing device performs ground plane removal based on range to detect targets and perform local sensor fusion. The local computing device may use a global nearest neighbor (GNN) algorithm and a Kalman filter. The local computing device may create an HD map or the data may be brought together with other target data at a central computing device to produce the HD map. Vehicle position and motion are controlled based on the HD map. Detecting and removing a ground plane based on range are illustrated. Fusion, ground plane removal, and delay filtering may be used in various contexts, such as roadways, parking lots and shipping yards.

A computer includes a processor and a memory storing instructions executable by the processor to identify a current location of the vehicle in a map of a stopping area, collect data to calibrate a sensor while the vehicle is moving in the stopping area, calibrate the sensor based on the collected data, and actuate one or more vehicle components to move the vehicle to a stopping location in the stopping area based on the location of the vehicle in the map and data collected by the calibrated sensor.

A vehicle is determined to be in a parking area based on vehicle sensor data. A mapping operation mode is activated based on determining the vehicle is in the parking area. A travel path of the vehicle through the parking area is recorded based on receiving a user input selecting the mapping operation mode. A map of the parking area is updated based on the recorded travel path.

An approach is provided for requesting a map update based on an accident and/or damaged/malfunctioning sensors to allow a vehicle to continue driving. The approach involves determining, by one or more processors, a status of one or more sensors, one or more systems, or a combination thereof of a vehicle. The approach also involves transmitting, by the one or more processors, a request for a map update based on the status of the one or more sensors, the one or more systems, or a combination thereof of the vehicle. The approach further involves receiving, by the one or more processors, the map update in response to the request. The approach further involves configuring, by the one or more processors, at least one system of the vehicle to operate using the map update.

This application provides a map update method, an apparatus, and a storage medium related to the navigation field. The method includes: matching, by a first vehicle, environmental data collected by a data collection apparatus on the first vehicle with prestored map data, and when it is determined that the environmental data does not match the map data, reporting map update information to a cloud server, where the map update information includes related information of a to-be-updated map element; and determining, by the cloud server based on the map update information reported by the first vehicle, whether to update a map, and when the map is determined to be updated, determining a delivery manner of an updated map based on an impact level that is of vehicle traveling and that corresponds to the to-be-updated map element. The foregoing method can be used to improve traveling safety of the automatic driving vehicle.

Systems and methods for managing environmental conditions for an autonomous vehicle are disclosed. In one aspect, an autonomous vehicle includes a perception sensor configured to generate perception data indicative of a condition of the environment, a network communication transceiver configured to communicate with an oversight system and an external weather condition source, a non-transitory computer readable medium, and a processor. The processor is configured to: receive the perception data from the at least one perception sensor, receive an indication of current weather conditions from the external weather condition source, determine a current environmental condition severity level from a plurality of severity levels based on the perception data and the indication of current weather conditions, modify one or more driving parameters that that govern a range of actions that can be autonomously executed by the autonomous vehicle, and navigate the autonomous vehicle based on the modified driving parameters.

A navigation system for a host vehicle may include a processor programmed to: receive from a center camera onboard the host vehicle a captured center image including a representation of at least a portion of an environment of the host vehicle, receive from a left surround camera onboard the host vehicle a captured left surround image including a representation of at least a portion of the environment of the host vehicle, and receive from a right surround camera onboard the host vehicle a captured right surround image including a representation of at least a portion of the environment of the host vehicle; provide the center image, the left surround image, and the right surround image to an analysis module configured to generate an output relative to the at least one captured center image; and cause a navigational action by the host vehicle based on the generated output.

Computer implemented methods and systems for deploying response vehicles based on a virtual environment. A server may obtain a virtual model of an overall region wherein the virtual model was generated based upon a plurality of images captured by a remote imaging vehicle. The server may then provide the virtual model to a user electronic device for rendering in a virtual environment. The server may then determine a target location within the overall region at which the response vehicle should be deployed and generate a route for the response vehicle to follow. The route may be based on damage indicated by the virtual model of the overall region. The server may then provide the route to the user electronic device and/or the response vehicle.