Proactive, knowledge‐based intelligent transportation system based on vehicular sensor networks. Issue 4 (1st December 2013)

• Record Type: Journal Article
• Authors: Dimitrakopoulos, George; Bravos, George; Nikolaidou, Mara; Anagnostopoulos, Dimosthenis
• Is Part Of: IET intelligent transport systems. Volume 7:Issue 4(2013)
• Page Start: 454
• Page End: 463
• Publication Date: 2013-12-01
• Subjects: automated highways -- driver information systems -- Internet -- knowledge based systems -- mobile radio -- road accidents -- road traffic -- transportation -- wireless sensor networks -- emergency management; information and communication technologies -- ICT -- future Internet era -- complex network infrastructures -- innovative applications -- traffic congestions -- emergencies -- accidents -- transportation infrastructures -- emergency management -- vehicular sensor networks -- intelligent information processing -- proactive knowledge‐based intelligent transportation system -- traffic management; Intelligent transportation systems -- Periodicals; Electronics in transportation -- Periodicals; 388.31205
• DOI: 10.1049/iet-its.2012.0138
• Languages: English
• ISSNs: 1751-956X

Abstract

Abstract : Information and Communication Technologies (ICT) rapidly migrate towards the Future Internet era, which is characterised, among others, by powerful and complex network infrastructures and innovative applications, services and content. An application area that attracts immense research interest is transportation. In particular, traffic congestions, emergencies and accidents reveal inefficiencies in transportation infrastructures, which can be overcome through the exploitation of ICT findings, in designing systems that are targeted at traffic/emergency management, namely Intelligent Transportation Systems. This study presents such a system that operates on the basis of collecting information from various sources (vehicles and infrastructure objects) through vehicular sensor networks, intelligently processing it, integrating knowledge and experience coming from the past and, finally, issuing directives to the driver for facilitating transportation. The overall approach is presented in detail, whereas a novel heuristic is proposed for the algorithmic process towards reaching decisions. Indicative simulation results showcase its efficiency, mostly with regards to proactively identifying a potential forthcoming danger and accordingly notifying the driver.