2008 11th International IEEE Conference on Intelligent Transportation Systems 2008
DOI: 10.1109/itsc.2008.4732537
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Analysis of Vehicle Lane Changes for Determining Fastest Paths in the V2V2I ITS Architecture

Abstract: In this paper I perform an analysis of vehicle lane changes and how they relate to fastest path determination. I converted live discrete loop detector data from the California Department of Transportation into continuous data to be utilized by vehicles in a vehicle-to-vehicle-to-infrastructure (V2V2I) intelligent transportation system (ITS) architecture.The continuous data was then used by FreeSim (http://www.freewaysimulator.com) to simulate live traffic conditions. As the time to traverse the edges in the tr… Show more

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Cited by 3 publications
(1 citation statement)
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“…In [13], for the first time, a 0018-9545 © 2013 IEEE vehicle-to-vehicle-to-infrastructure (V2V2I) architecture for vehicular networks, which is a hybrid of V2I and V2V architectures, is described. A super-vehicle algorithm is then proposed in [14] for the V2V2I communication system, where the vehicular network is broken into several preconfigured zones, and in each zone, there exists a super vehicle. The super vehicle can receive data from all of the other vehicles within its zone, aggregate the data, and then transmit the aggregated data to the central server or other super vehicles in adjacent zones.…”
Section: Introductionmentioning
confidence: 99%
“…In [13], for the first time, a 0018-9545 © 2013 IEEE vehicle-to-vehicle-to-infrastructure (V2V2I) architecture for vehicular networks, which is a hybrid of V2I and V2V architectures, is described. A super-vehicle algorithm is then proposed in [14] for the V2V2I communication system, where the vehicular network is broken into several preconfigured zones, and in each zone, there exists a super vehicle. The super vehicle can receive data from all of the other vehicles within its zone, aggregate the data, and then transmit the aggregated data to the central server or other super vehicles in adjacent zones.…”
Section: Introductionmentioning
confidence: 99%