Intelligent Transportation Systems (ITS) are changing the way people plan a journey and travel around the world. Advanced mobility information systems, as well as intelligent multimodal mobility services, may take considerable advantage of consolidated technologies from emerging ICT frameworks. In this paper we propose an Extended Intelligent Transportation System (ExITS) consisting of a basic ITS equipped with a User Centric Control System (UCCS). The proposed ExITS relies on service personalization methodologies and is conceived as a Future Internet (FI) oriented, closed-loop, user centric architecture integrating and controlling ITS services. The proposed UCCS considers the trip planning service and takes into account both explicit and implicit user preferences in selecting travel solutions satisfying a given user request. The aim of the UCCS is to drive the trip planning service in proposing to the user travel typologies tailored to personal preferences. Implicit preferences are automatically inducted by similarity based unsupervised machine learning techniques and verified by a closed-loop control mechanism triggered by explicit user feedback.
A Future Internet oriented user centric extended intelligent transportation system
RICCIARDI CELSI L;
2016-01-01
Abstract
Intelligent Transportation Systems (ITS) are changing the way people plan a journey and travel around the world. Advanced mobility information systems, as well as intelligent multimodal mobility services, may take considerable advantage of consolidated technologies from emerging ICT frameworks. In this paper we propose an Extended Intelligent Transportation System (ExITS) consisting of a basic ITS equipped with a User Centric Control System (UCCS). The proposed ExITS relies on service personalization methodologies and is conceived as a Future Internet (FI) oriented, closed-loop, user centric architecture integrating and controlling ITS services. The proposed UCCS considers the trip planning service and takes into account both explicit and implicit user preferences in selecting travel solutions satisfying a given user request. The aim of the UCCS is to drive the trip planning service in proposing to the user travel typologies tailored to personal preferences. Implicit preferences are automatically inducted by similarity based unsupervised machine learning techniques and verified by a closed-loop control mechanism triggered by explicit user feedback.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
