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Towards using microscopic traffic simulations for safety evaluation
KTH, School of Engineering Sciences (SCI), Aeronautical and Vehicle Engineering, Vehicle Dynamics.
2018 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Microscopic traffic simulation has become an important tool to investigate traffic efficiency and road safety. In order to produce meaningful results, incorporated driver behaviour models need to be carefully calibrated to represent real world conditions. In addition to macroscopic relationships such as the speed-density diagram, they should also adequately represent the average risk of accidents occurring on the road. In this thesis, I present a two stage computationally feasible multi-objective calibration process. The first stage performs a parameter sensitivity analysis to select only parameters with considerable effect on the respective objective functions to keep the computational complexity of the calibration at a manageable level. The second stage employs a multi-objective genetic algorithm that produces a front of Pareto optimal solutions with respect to the objective functions. Compared to traditional methods which focus on only one objective while sacrificing accuracy of the other, my method achieves a high degree of realism for both traffic flow and average risk.

Abstract [sv]

Mikroskopisk trafiksimulering har blivit ett viktigt verktyg för att undersöka trafik effektivitet och trafiksäkerhet. För att producera meningsfulla resultat måste inbyggda drivrutinsbeteendemodeller noggrant kalibreras för att representera verkliga förhållanden i världen. Förutom makroskopiska relationer, såsom hastighetsdensitetsdiagrammet, bör de också på ett adekvat sätt representera den genomsnittliga risken för olyckor som uppträder på vägen. I denna avhandling presenterar jag en tvåstegs beräkningsberättigbar mångsidig kalibreringsprocess. Det första steget utför en parameterkänslighetsanalysför att bara välja parametrar med stor effekt på respektive objektiv funktioner för att hålla kalibrerings komplexiteten på en hanterbar nivå. Det andra steget använder en mångriktig genetisk algoritm som ger framsidan av Pareto optimala lösningar med hänsyn till objektivfunktionerna. Jämfört med traditionella metoder som fokuserar på endast ett mål, samtidigt som man offrar den andra, ger min metod en hög grad av realism för både trafikflöde och genomsnittlig risk.

Place, publisher, year, edition, pages
2018. , p. 65
Series
TRITA-SCI-GRU ; 2018:380
Keywords [en]
Calibration, Microscopic Traffic Simulation, Multiple Objective, Genetic Algorithm, Traffic Flow, Highway Safety
Keywords [sv]
Kalibrering, Mikroskopisk trafiksimulering, Flera objektiv, Genetisk algoritm, Trafikflöde, Motorvägsäkerhet
National Category
Vehicle Engineering
Identifiers
URN: urn:nbn:se:kth:diva-243486OAI: oai:DiVA.org:kth-243486DiVA, id: diva2:1285789
External cooperation
Tumcreate
Examiners
Available from: 2019-02-05 Created: 2019-02-05 Last updated: 2019-02-05Bibliographically approved

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CiteExportLink to record
Permanent link

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Citation style
  • apa
  • harvard1
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  • modern-language-association-8th-edition
  • vancouver
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Language
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  • Other locale
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Output format
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