A parking assistance device includes a traveling route setting unit, a traveling route supply unit, an information acquiring unit, and a determination unit. The traveling route setting unit is configured to set a traveling route from a position of a vehicle to a parking spot in a parking lot. The traveling route supply unit is configured to supply information indicating the traveling route to the vehicle. The information acquiring unit is configured to acquire situation information containing the position of the vehicle and a situation of the parking lot. The determination unit is configured to determine whether the traveling route needs to be reset based on the situation information. When the determination unit determines that the traveling route needs to be reset, the traveling route setting unit resets the traveling route based on the situation information, and the traveling route supply unit supplies information indicating the reset traveling route.

A mobile body such that a parking lot management center specifies a parking place for the mobile body and the mobile body moves to the specified parking place, wherein the mobile body includes an automatic valet parking management device that, when the mobile body moves to the parking place but the mobile body cannot park in the parking place, requests a new parking place for the mobile body from the parking lot management center.

An automated parking system for a vehicle according to an exemplary embodiment of this disclosure includes, among other possible things, a camera configured to obtain images of objects proximate the vehicle, and a controller configured to review the obtained images of objects proximate the vehicle to classify a location of the vehicle, determine a height of overhead objects associated with the classified location and initiate an automated parking function of the vehicle that corresponds to the determined height of the overhead objects.

Embodiments described herein relate to anonymization of parking events such that parking events may be used by location-based service providers without revealing a target associated with the respective parking events. Methods may include: receiving an indication of a parking event; map-matching the parking event to a parking event road segment; identifying candidate road segments, wherein the candidate road segments are connected directly or indirectly to the parking event road segment; selecting a road segment of the candidate road segments; updating the parking event to be an updated parking event associated with the selected road segment; and providing the updated parking event to a location-based service provider.

A parking guidance method based on temporal and spatial features and its device, equipment, and storage medium, wherein the said method consists of two steps: accessing the estimated driving information of the targeted vehicles (S101), where the estimated driving information includes the targeted vehicle's planned driving route, destination and estimated time of arrival; inputting the estimated driving information into the pre-trained city-wide parking guidance system to generate recommended parking lot information for the targeted vehicle, where the city-wide parking guidance system is a spatiotemporal classifier trained with the parking events of urban cities in the current city as the training data (S102). The said method eliminates the necessity of relying on parking data from urban parking lots and effectively improves the city-wide parking guidance effect.

A method for performing correlation-based parking availability estimation is provided. The method includes retrieving a plurality of parking availability correlation models, wherein each of the parking availability correlation models estimates parking availability for a target parking block based on parking availability for one or more other parking blocks; selecting a subset of the parking availability correlation models, wherein the subset comprises parking availability correlation models that estimate parking availability of the target parking block based on parking availability for one or more other parking blocks for which current parking availability is known; selecting a parking availability correlation model from the subset based on a model quality indicator associated with each parking availability correlation model; and estimating parking availability for the target parking block based on the selected parking availability correlation model.

This invention concerns a system and a method for the management of delimited areas distributed on a territory. A predisposition of a plurality devices distributed on the territory is provided, each one capable of monitoring a predetermined area, each distributed device being of an “embedded” type and includes: a local “embedded” processor connected to at least one video camera positioned nearby and from which it acquires the images that it processes according to a “deep learning” module and “Computer Vision” technique. The deep learning model is based on a CNN (computer neural network) for the detection of vehicles occupying spaces and the identification of areas that can be occupied, both in delimited areas with a defined layout and in areas with an undefined layout, the data processed being sent to a central unit via an Internet network in one example.

An approach is provided for providing an isoline map of a time to park at a destination. A routing platform computes the time to park at a destination of a navigation route, wherein the time to park represents an estimated time that is needed for a vehicle to park within a geographic area surrounding the destination. The routing platform further determines an isoline that delineates a boundary of the geographic area, wherein the isoline indicates an extent of the geographic area in which the time to park applies. The routing platform further provide data to generate a user interface depicting a representation of the isoline in the time to park isoline map.

Contemporary navigation systems are often tasked with routing a vehicle to a destination, but are poorly equipped to assist with finding a vacancy of a parking opportunity in which the vehicle may be parked. Static information, such as enumeration of parking garages and curbside parking meters, may be frustrating if such parking opportunities have no vacancies. The determination of vacancies with certainty may be difficult to achieve due to the characteristic volatility of parking, in which vacancies may be taken in seconds. Presented herein are navigation device configurations involving probabilistic evaluation of parking routes in a vicinity of a destination that may be generated and compared, optionally weighted by various factors, to identify a parking route with parking opportunities that collectively present a high probability of vacancy as compared with other parking routes, which may be presented to the user and/or appended to a current route of an autonomous vehicle.

Lighting fixture data hubs and systems and methods for use. An example of a data hub may include an annunciator configured to generate a first indication and a second indication, one or more sensors configured to detect between one or more vehicles and one or more pedestrians and potential convergence thereof within a zone in a vicinity of the data hub and to emit one or more signals corresponding to said detection, and a gateway in communication with an on-board processor and the annunciator, the on-board processor configured to wirelessly receive and analyze the one or more signals, communicate said one or more signals to the gateway so that the gateway can generate the first indication or the second indication in response to the one or more signals. Data hubs may also include a sensor unit housing and/or a light source.