Latest revision as of 04:06, 2 February 2021

Abstract

PUBLISHED

Public transport vehicles often share a road network with other road users making their journeys susceptive to changing road conditions and especially to congestion. Travelers using such public transport increasingly depend on real-time information to plan their journeys. While such information can be provided by Automatic Vehicle Location (AVL) systems, AVLs depend heavily on large-scale deployment of designated sensory equipment, which may prevent their pervasive adoption. This paper presents a system for estimating vehicle location based on information generated by data sources typically integrated within existing ITS platforms. This enables location estimation for public transport vehicles without the need for deploying a designated sensor infrastructure in each vehicle, thereby reducing deployment and maintenance cost significantly. A prototypical vehicle location estimation system has been realized as part of and using data provided by the iTransIT ITS framework. Initial evaluation results show that such a system is feasible in a distributed manner and that estimated results are within 20% compared to empirical data.

The work described in this paper was partly supported by Lero - the Irish Software Engineering Research Centre. SFI)

Original document

The different versions of the original document can be found in:

• http://hdl.handle.net/10344/2119

• https://ulir.ul.ie/bitstream/10344/2119/2/2008_Morenz.pdf

• http://hdl.handle.net/2262/36086,

http://dx.doi.org/10.1109/ITSC.2008.4732654

• http://xplorestaging.ieee.org/ielx5/4721641/4732517/04732654.pdf?arnumber=4732654,

http://dx.doi.org/10.1109/itsc.2008.4732654

• https://dblp.uni-trier.de/db/conf/itsc/itsc2008.html#MorenzM08,

http://www.tara.tcd.ie/handle/2262/36086,

http://yadda.icm.edu.pl/yadda/element/bwmeta1.element.ieee-000004732654,

https://ulir.ul.ie/handle/10344/2119,

http://www.tara.tcd.ie/bitstream/handle/2262/36086/An%20Estimation.pdf?sequence=1,

https://ieeexplore.ieee.org/document/4732654,

https://trid.trb.org/view/1365726,

https://academic.microsoft.com/#/detail/2161772326