International Business Machines Corporation

University College Dublin

Claudio Gambella

Yassine Lassoued

Julien Monteil

Martin Mevissen

Rodrigo Hernan Ordonez-Hurtado

Robert Shorten

Giovanni Russo

Jakub Marecek

Jonathan P Epperlein

Wynita M Griggs

Anton Dekusar

Bei Chen

Sergiy Zhuk

Andrea Simonetto

Sergio Cabrero Barros

Jonathan Peter Epperlein

Wynita May Griggs

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 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

In an approach for determining the illumination necessary along a vehicle's planned trajectory, a processor receives information relevant to the trajectory of a vehicle. A processor estimates the position of the vehicle at the particular time on the trajectory of the vehicle, using the data from the sensors. A processor estimates an illumination of the trajectory of the vehicle, using the model of the illumination of the road network and the data from the sensors, wherein a threshold is employed. A processor determines the threshold is exceeded. A processor changes a setting of the at least one headlight on the vehicle. A processor determines the threshold is exceeded. A processor alerts the user of the vehicle when adjustments to the at least one headlight that are necessary to illuminate the trajectory of the vehicle exceed physical limitations of the at least one headlight.

Adaptive headlights for the trajectory of a vehicle

A system and method for cognitive journey monitoring are presented. Embodiments comprise journey prediction, parsing of data sources, risk assessment and mitigation, and natural-language user interaction by a cognitive processor. Data is gathered from a plurality of data sources and analyzed in the context of one or more of the user's intention(s). A dialogue with the user, in natural language, aims to provide and select one or more suggestions relating to the one or more user intention(s) such that the risk(s) relating to the one or more user's intention(s) is reduced. During the dialogue, cognitive reasoning may be performed, wherein the cognitive reasoning includes the ability to justify each suggestion and the ability to infer information from the interaction such as, for example, data obtained in a dialogue may inform subsequent inferences. The embodiments may use speech synthesis and speech recognition in an interactive spoken dialogue.

Cognitive journey companion system

Embodiments for testing embedded systems and their applications in an Internet of Things (IoT) environment by a processor, denoted as a Hardware-in-the-Loop as a Service (HiLaaS). In a simulated environment, one or more simulated entities and one or more real entities in a networked system may be tested in real-time according to received control parameters, for a price. The price is estimated by the system, based on other parameters, and offered to the user to accept or reject. Alternatively, the user may specify the price, the system estimates control parameters, and the user can accept or reject the control parameters. One or more properties of the one or more entities, the network system, or combination thereof may be estimated based on the testing of the one or more simulated entities, when the price and control parameters are accepted.

Testing embedded systems and application using hardware-in-the-loop as a service (HILAAS)

A system and method for cognitive risk mitigation are presented. Embodiments comprise journey prediction, parsing of data sources, risk assessment and mitigation, and natural-language user interaction by a cognitive processor. Data is gathered from a plurality of data sources and analyzed in the context of one or more of the user's intention(s). A dialogue with the user, in natural language, aims to provide and select one or more suggestions relating to the one or more user intention(s) such that the risk(s) relating to the one or more user's intention(s) is reduced. During the dialogue, cognitive reasoning may be performed, wherein the cognitive reasoning includes the ability to justify each suggestion and the ability to infer information from the interaction such as, for example, data obtained in a dialogue may inform subsequent inferences. The embodiments may use speech synthesis and speech recognition in an interactive spoken dialogue.

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Dublin, Ireland

Claudio Gambella