A vehicle-to-everything (V2X) communication system is provided with a user interface for displaying content within a host vehicle and at least one transceiver to receive input indicative of the host vehicle turning at an upcoming intersection, and input indicative of driving conditions within a region between a remote vehicle and the upcoming intersection. A processor is programmed to determine a passing maneuver feasibility based on the driving conditions in response to the host vehicle initiating a passing maneuver relative to the remote vehicle, and to generate a driver assist message on the user interface based on the passing maneuver feasibility.

This document describes techniques and systems for crowd-sourced continuous update data collection for automotive applications. Each vehicle of a vehicle fleet may include a logging system, a data query daemon, and a user application. The logging system logs application metadata or sensor data for a host vehicle. The data query daemon receives data queries from a remote data query system and detects the requested data in the application metadata and/or the sensor data being logged. The user application may provide information related to the data query to the vehicle user and request permission to execute the data query. In this way, application providers for ADAS and AD systems may collect relevant data from an existing vehicle fleet to develop updated or new applications without incurring the recurring cost of expensive data collection campaigns.

A method for automatically learning parking preferences for a driver and generating parking recommendations includes generating training data based at least in part on: 1) trajectory data indicating a trajectory of a vehicle during a plurality of parking events, each in which a driver of the vehicle selected a parking candidate from among a plurality of parking candidates, and 2) attribute data indicating attributes of each of the plurality of parking candidates, removing, from the training data, data associated with at least one available parking candidate based on one or more conditions that indicate the driver did not consider the at least one available parking candidate, and training a decision model, based on remaining training data, to estimate a preferred parking candidate for the driver from among a set of available parking candidates.

The disclosed technology provides solutions for facilitating the selection of a parking space by a user of a parking application. A process of the disclosed technology can include steps for monitoring sensor data and location data associated with a user device, retrieving, based on the location data associated with a user device, listing data associated with one or more parking spaces in a vicinity of the user device, and capturing image data that includes at least a portion of the one or more parking spaces. In some aspects, the process may further include steps for overlaying one or more graphical objects onto the image data, wherein the one or more graphical objects are based on the listing data associated with the one or more parking spaces. Systems and machine-readable media are also provided.

Techniques are provided for autonomous vehicle fleet management for reduced traffic congestion. A request is received for a vehicular ride. The request includes an initial spatiotemporal location and a destination spatiotemporal location. A processor is used to generate a representation of lane segments. Each lane segment is weighted in accordance with a number of other vehicles on the lane segment. A vehicle located within a threshold distance to the initial spatiotemporal location is identified such that the identified vehicle has at least one vacant seat. The processor is used to determine a route for operating the identified vehicle from the initial spatiotemporal location to the destination spatiotemporal location. The route includes one or more lane segments of the lane segments. An aggregate of weights of the one or more lane segments is below a threshold value. The received request and the determined route are transmitted to the identified vehicle.

Aspects of the present disclosure describe systems, methods, and devices for automated vehicular control based on glare detected by an optical system of a vehicle. In some aspects, automated control includes controlling the operation of the vehicle itself, a vehicle subsystem, or a vehicle component based on a level of glare detected. According to some examples, controlling the operation of a vehicle includes instructing an automatically or manually operated vehicle to traverse a selected route based on levels of glare detected or expected along potentials routes to a destination. According to other examples, controlling operation of a vehicle subsystem or a vehicle component includes triggering automated responses by the subsystem or the component based on a level of glare detected or expected. In some additional aspects, glare data is shared between individual vehicles and with a remote data processing system for further analysis and action.

A system for managing vehicles includes a plurality of first level managers, and a plurality of second level managers each being in a higher hierarchical level than the plurality of first level managers and managing a section. Each of the plurality of first level managers collects data using one or more sensors of a vehicle, abstracts the data to obtain first information, and transmits a first instruction to the vehicle based on the first information. One of the plurality of second level managers receives the first information from one or more of the plurality of first level managers in the section managed by the one of the plurality of second level managers, obtains second information based on the first information, and transmits a second instruction to the vehicle based on the second information. The first instruction is different from the second instruction.

A computer-implemented method and system for usage-controlled service delivery to an onboard system of a vehicle are designed for delivering updatable services to the onboard system of the vehicle by way of a vehicle-external server according to data of the service usage behavior of a vehicle user of the updatable services.

A method includes receiving vehicle data for a plurality of vehicles in a parking facility over time, the vehicle data including a time t1 indicating when each of the vehicles leaves its corresponding parking spot in the parking facility, and a time t2 indicating when each of the plurality of vehicles reaches an exit of the parking facility. An egress time is determined for each of the plurality of vehicles based at least in part on the corresponding times t1 and t2. A timestamp is assigned to each of the egress times, resulting in timestamped egress times. A current egress time of the parking facility is estimated based at least in part on the timestamped egress times. An action recommendation is based at least in part on the current egress time of the parking facility and is outputted for subsequent viewing by the driver of the particular vehicle.

Systems and methods for generating calm or quiet routes are provided. When a user requests navigation directions and indicates a preference for a calm route, a plurality of routes between the origin location and the destination location requested by the user may be identified. Historical sensor data (e.g., including heart rate data, exterior vehicle noise level data, accelerometer data) and traffic data associated with route segments of each of the routes may be analyzed to identify indications of calmness associated with each route segment. Current traffic data associated with the route segments may be analyzed to assign a traffic score representing a level of congestion along the segment and corresponding to a level of insurance risk associated with traversing the segment. Based at least in part upon the indications of calmness and the traffic score associated with each route segment, a route may be selected and presented to the user.