International Business Machines Corporation

Anton Dekusar

Yassine Lassoued

Julien Monteil

Martin Mevissen

Rodrigo Hernan Ordonez-Hurtado

Claudio Gambella

Bei Chen

Sergiy Zhuk

Robert Shorten

Giovanni Russo

Andrea Simonetto

Wynita M Griggs

Sergio Cabrero Barros

An embodiment for dynamically assigning vehicle parking is provided. The embodiment may include receiving one or more preferences regarding parking. The embodiment may also include in response to determining a detector vehicle detects a vacant parking spot, creating a network of vehicles within a pre-defined threshold of the vacant parking spot. The embodiment may further include notifying each vehicle in the network about the vacant parking spot and receiving one or more requests for the vacant parking spot from one or more requestor vehicles. The embodiment may also include identifying real-time information associated with roads within the pre-defined threshold of the vacant parking spot. The embodiment may further include assigning the vacant parking spot to a particular requestor vehicle in the network of vehicles. The embodiment may also include displaying an indicator placed adjacent to the particular requestor vehicle that is assigned the vacant parking spot.

Dynamic vehicle parking assignment with user feedback

Embodiments for implementing intelligent risk detection and mitigation in a transport network by a processor. Data gathered from a plurality of data sources relating to an entity and a selected region of interest may be analyzed. Behavior of an entity, in relation to a risk event, may be learned and interpreted based on a plurality of identified contextual factors, geographical data, current data, historical data, a learned risk event model, or a combination thereof. One or more mitigation actions may be performed to mitigate risk of occurrence or a possible negative impact of the risk event caused at least in part by the behavior of the entity.

Detecting and mitigating risk in a transport network

Embodiments for providing intelligent transportation service management in a transportation system by a processor. Transportation service requests may be assigned amongst multiple transportation service providers according to one or more transportation service request distribution models and various parameters and preferences for each user. The transportation service request distribution models may protect information relation to each of the transportation service providers and suggests a selected order for distributing the plurality of transportation service requests.

Intelligent on-demand management of ride sharing in a transportation system

Generating parking area statistics for identifying parking areas within a geographic region. Navigation support for reaching a top-ranked parking area according to collected parking area data, user preferences, parking feedback, and real-time traffic conditions. Selection of a top-ranked parking area and monitoring progress during a parking event improve future identification and ranking of parking areas.

Identifying available parking areas

Embodiments for planning vehicular driving actions in the presence of non-recurrent events by a processor. One or more dynamics of non-recurrent events in a transport network may be learned according to one or more contextual factors. One or more vehicle-specific factors may be learned in relation to a historical journey and current journey of a vehicle. One or more action responses associated with the one or more non-recurrent events and the one or more vehicle-specific factors may be generated.

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Castleknock, Ireland

Anton Dekusar