Journal article
Study of a geo-multicast framework for efficient message dissemination at unmanned level crossings
IET Intelligent Transport Systems, Vol.8(4), pp.425-434
2014
Abstract
Collisions among trains and cars at road/rail level crossings (LXs) can have severe consequences such as high level of fatalities, injuries and significant financial losses. As communication and positioning technologies have significantly advanced, implementing vehicular ad hoc networks (VANETs) in vicinity of unmanned LXs, generally LXs without barriers, is seen as an efficient and effective approach to mitigate or even eliminate collisions without imposing huge infrastructure costs. VANETs necessitate unique communication strategies, in which routing protocols take a prominent part in their scalability and overall performance, through finding optimised routes quickly and with low bandwidth overheads. This article studies a novel geo-multicast framework that incorporates a set of models for communication, message flow and geo-determination of endangered vehicles with a reliable receiver-based geo-multicast protocol to support cooperative level crossings (CLXs), which provide collision warnings to the endangered motorists facing road/rail LXs without barriers. This framework is designed and studied as part of a $5.5 m Government and industry funded project, entitled 'Intelligent-Transport-Systems to improve safety at road/rail crossings'. Combined simulation and experimental studies of the proposed geo-multicast framework have demonstrated promising outcomes as cooperative awareness messages provide actionable critical information to endangered drivers who are identified by CLXs.
Details
- Title
- Study of a geo-multicast framework for efficient message dissemination at unmanned level crossings
- Authors
- Keyvan Ansari (Author) - Queensland University of TechnologyYanming Feng (Author) - Queensland University of TechnologyJack Singh (Author) - La Trobe University
- Publication details
- IET Intelligent Transport Systems, Vol.8(4), pp.425-434
- Publisher
- IEEE (Institute of Electrical and Electronics Engineers)
- Date published
- 2014
- DOI
- 10.1049/iet-its.2013.0061
- ISSN
- 1751-956X
- Organisation Unit
- University of the Sunshine Coast, Queensland; USC Business School - Legacy; School of Science, Technology and Engineering
- Language
- English
- Record Identifier
- 99450708402621
- Output Type
- Journal article
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