Comprehensive performance analysis and comparison of vehicles routing algorithms in smart cities

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Title: Comprehensive performance analysis and comparison of vehicles routing algorithms in smart cities
Authors: Wang, ShenDjahel, SoufieneMcManis, JenniferMcKenna, CormacMurphy, Liam, B.E.
Permanent link: http://hdl.handle.net/10197/11317
Date: 31-Oct-2013
Online since: 2020-03-16T12:17:22Z
Abstract: Due to the severe impact of road traffic congestion on both economy and environment, several vehicles routing algorithms have been proposed to optimize travelers itinerary based on real-time traffic feeds or historical data. However, their evaluation methodologies are not as compelling as their key design idea because none of them had been tested under both real transportation map and real traffic data. In this paper, we conduct a deep performance analysis and comparison of four typical vehicles routing algorithms under various scalability levels (i.e. trip length and traffic load) based on realistic transportation simulation. The ultimate goal of this work is to suggest the most suitable routing algorithm to use in different transportation scenarios, so that it can provide a valuable reference for both traffic managers and researchers when they deploy or optimize a large scale centralized Traffic Management System (TMS). The obtained simulation results reveal that dynamic A* is the best routing algorithm if the TMS has sufficient memory or storage capacities, otherwise static A* is also a great alternative.
Funding Details: Science Foundation Ireland
Type of material: Conference Publication
Publisher: IEEE
Copyright (published version): 2013 IEEE
Keywords: Heuristic algorithmsVehiclesRoadsRoutingVehicle dynamicsMeasurementAlgorithm designAlgorithm analysis
DOI: 10.1109/giis.2013.6684365
Language: en
Status of Item: Peer reviewed
Is part of: Global Information Infrastructure Symposium - GIIS 2013
Conference Details: The 2013 Global Information Infrastructure Symposium (GIIIS 2013), Trento, Italy, 28-31 October 2013
ISBN: 978-1-4799-2969-6/13
Appears in Collections:Computer Science Research Collection

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