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Swarm-based Traffic Lights Policy Selection

Belletti, Riccardo and Bonfietti, Alessio and Foschini, Luca and Milano, Michela and Krajzewicz, Daniel (2014) Swarm-based Traffic Lights Policy Selection. In: 4th ACM Symposium on Development and Analysis of Intelligent Vehicular Networks and Applications, DIVANet 2014. Fourth ACM International Symposium on Design and Analysis of Intelligent Vehicular Networks and Applications (DIVANet’14), 2014-09-21 - 2014-09-26, Montreal, Canada. doi: 10.1145/2656346.2656364. ISBN 978-1-4503-3028-2.

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Abstract

Improving the efficiency of urban vehicular mobility, also via the optimized management of the dynamic behavior of traffic lights with limited infrastructure investments and limited operational costs, is widely recognized as a crucial goal for smart cities, capable of relevant economic impacts in terms of travel time/cost reduction and better sustainability. Within this context, in the framework of the ongoing EU FP7 COLOMBO project, we are investigating, developing, and thoroughly evaluating innovative locality-based vehicular cooperation protocols for the determination of traffic characteristics in proximity of intersections, with no need for communication towards global data collection centers. One of the specific and original goals in COLOMBO is to achieve reasonable and sufficiently accurate traffic estimations with limited penetration rates of actively participating vehicles equipped with differentiated V2X capabilities (full-fledged V2X-enabled cars but also vehicles with only onboard smartphones). In this paper, we specifically focus on our recent research work of implementation and evaluation of our protocols on top of the iTETRIS simulation platform, a state-of-the-art integrated platform resulted from the synergic interworking of the ns-3 network and the SUMO vehicular mobility simulators. In particular, here we originally describe how to effectively and efficiently implement V2X protocols on iTETRIS, as well as lessons learned from our practical experience of deployment, evaluation, and protocol/iTETRIS fine-tuning. The reported simulation results (obtained through realistic simulations based on real traffic traces and the real road topology of the city of Bologna) show the feasibility of the proposed approach also with very limited penetration rates.

Item URL in elib:https://elib.dlr.de/91055/
Document Type:Conference or Workshop Item (Speech)
Title:Swarm-based Traffic Lights Policy Selection
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Belletti, RiccardoUniversity of BolognaUNSPECIFIEDUNSPECIFIED
Bonfietti, AlessioUniversity of BolognaUNSPECIFIEDUNSPECIFIED
Foschini, LucaUniversity of BolognaUNSPECIFIEDUNSPECIFIED
Milano, MichelaUniversity of BolognaUNSPECIFIEDUNSPECIFIED
Krajzewicz, DanielUNSPECIFIEDhttps://orcid.org/0000-0003-1045-8800UNSPECIFIED
Date:21 September 2014
Journal or Publication Title:4th ACM Symposium on Development and Analysis of Intelligent Vehicular Networks and Applications, DIVANet 2014
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:No
DOI:10.1145/2656346.2656364
ISBN:978-1-4503-3028-2
Status:Published
Keywords:Traffic Monitoring, V2V Communications, Vehicular Peer-to-Peer Cooperation, SUMO & ns-3 Simulations, Limited Penetration Rate
Event Title:Fourth ACM International Symposium on Design and Analysis of Intelligent Vehicular Networks and Applications (DIVANet’14)
Event Location:Montreal, Canada
Event Type:international Conference
Event Start Date:21 September 2014
Event End Date:26 September 2014
Organizer:ACM
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Transport
HGF - Program Themes:Traffic Management (old)
DLR - Research area:Transport
DLR - Program:V VM - Verkehrsmanagement
DLR - Research theme (Project):V - MM2M - Mobilitätsmanagement für Morgen (old)
Location: Berlin-Adlershof
Institutes and Institutions:Institute of Transportation Systems > Verkehrssimulation und -prognose
Deposited By: Krajzewicz, Daniel
Deposited On:14 Oct 2014 14:50
Last Modified:24 Apr 2024 19:56

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