Abstract: One or more techniques and/or systems are provided for slowdown detection. Location data received from vehicles traveling a road is evaluated to identify a road segment associated with vehicle speeds below a threshold. A space-time diagram is generated, and location data associated with vehicles traveling the road segment are plotted within the space-time diagram. The space-time diagram is processed using a convolutional neural network to determine a probability that the space-time diagram illustrates a slowdown. If the probability that the space-time diagram illustrates the slowdown is greater than a threshold, then a notification of the slowdown is transmitted to one or more computing devices associated with vehicles that may encounter the slowdown.

Abstract: One or more techniques and/or systems are provided for slowdown detection. Location data received from vehicles traveling a road is evaluated to identify a road segment associated with vehicle speeds below a threshold. A space-time diagram is generated, and location data associated with vehicles traveling the road segment are plotted within the space-time diagram. The space-time diagram is processed using a convolutional neural network to determine a probability that the space-time diagram illustrates a slowdown. If the probability that the space-time diagram illustrates the slowdown is greater than a threshold, then a notification of the slowdown is transmitted to one or more computing devices associated with vehicles that may encounter the slowdown.

Abstract: One or more techniques and/or systems are provided for slowdown detection. Location data received from vehicles traveling a road is evaluated to identify a road segment associated with vehicle speeds below a threshold. A space-time diagram is generated, and location data associated with vehicles traveling the road segment are plotted within the space-time diagram. The space-time diagram is processed using a convolutional neural network to determine a probability that the space-time diagram illustrates a slowdown. If the probability that the space-time diagram illustrates the slowdown is greater than a threshold, then a notification of the slowdown is transmitted to one or more computing devices associated with vehicles that may encounter the slowdown.

Abstract: 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.

Abstract: One or more techniques and/or systems are provided for slowdown detection. Location data received from vehicles traveling a road is evaluated to identify a road segment associated with vehicle speeds below a threshold. A space-time diagram is generated, and location data associated with vehicles traveling the road segment are plotted within the space-time diagram. The space-time diagram is processed using a convolutional neural network to determine a probability that the space-time diagram illustrates a slowdown. If the probability that the space-time diagram illustrates the slowdown is greater than a threshold, then a notification of the slowdown is transmitted to one or more computing devices associated with vehicles that may encounter the slowdown.

Abstract: 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.

Abstract: One or more techniques and/or systems are provided for travel speed prediction. A spatial context of a prediction segment of a travel network for which a speed prediction is to be made is identified. The spatial context comprises one or more segments of the travel network that are part of trajectories of objects passing through the predication segment and that have predicted likelihoods of influencing travel speed along the prediction segment above a threshold. Features of the spatial context are formatted into a format compatible for input into the model based upon a structure of the model. The features are input into the model for processing using machine learning functionality to output the speed prediction for the prediction segment.

Abstract: One or more techniques and/or systems are provided for slowdown detection. Location data received from vehicles traveling a road is evaluated to identify a road segment associated with vehicle speeds below a threshold. A space-time diagram is generated, and location data associated with vehicles traveling the road segment are plotted within the space-time diagram. The space-time diagram is processed using a convolutional neural network to determine a probability that the space-time diagram illustrates a slowdown. If the probability that the space-time diagram illustrates the slowdown is greater than a threshold, then a notification of the slowdown is transmitted to one or more computing devices associated with vehicles that may encounter the slowdown.

Abstract: 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.

Abstract: Among other things, one or more techniques and/or systems are provided for authorizing an action using vehicle identification information (e.g., supplied by a vehicle) and user identification information (e.g., supplied by a mobile device associated with a user of the vehicle). Such an action may relate to, among other things, refueling the vehicle, parking the vehicle, using a fee-based road segment, and/or other vehicle-centric actions, for example. Moreover, in one embodiment, as part of the authorization, a payment transaction may be initiated by an authorization system configured to authorize the action.

Abstract: Among other things, one or more techniques and/or systems are provided for authorizing an action using vehicle identification information (e.g., supplied by a vehicle) and user identification information (e.g., supplied by a mobile device associated with a user of the vehicle). Such an action may relate to, among other things, refueling the vehicle, parking the vehicle, using a fee-based road segment, and/or other vehicle-centric actions, for example. Moreover, in one embodiment, as part of the authorization, a payment transaction may be initiated by an authorization system configured to authorize the action.