Anticipatory Adaptation of Signalisation Based on Traffic Flow Forecasts within a Self-organised Traffic Control System

Autonomously adapting signalling strategies to changing traffic demand in urban areas have been frequently used as application scenario for self-adapting systems. Striving for the ability to cope with the dynamic behaviour of traffic and to react appropriately to unforeseen conditions, such solution...

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Main Authors: Sommer Matthias, Hähner Jörg
Format: Article
Language:English
Published: EDP Sciences 2016-01-01
Series:MATEC Web of Conferences
Online Access:http://dx.doi.org/10.1051/matecconf/20168103006
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spelling doaj-885af10ba6d444199a17b9357310d6822021-02-02T03:55:41ZengEDP SciencesMATEC Web of Conferences2261-236X2016-01-01810300610.1051/matecconf/20168103006matecconf_ictte2016_03006Anticipatory Adaptation of Signalisation Based on Traffic Flow Forecasts within a Self-organised Traffic Control SystemSommer MatthiasHähner JörgAutonomously adapting signalling strategies to changing traffic demand in urban areas have been frequently used as application scenario for self-adapting systems. Striving for the ability to cope with the dynamic behaviour of traffic and to react appropriately to unforeseen conditions, such solutions dynamically adapt the signalisation to the monitored traffic demands. The Organic Traffic Control (OTC) system is one of the most prominent representatives in this domain. OTC implements a multi-layered observer-/controller architecture. In this paper, we extend OTC’s observer with a time series forecast component to create forecasts of future traffic developments for turning movements. These forecasts are then used to proactively adapt signalisation parameters. We demonstrate the benefit of the developed approach in terms of reduced travel times, and vehicle emissions within near-to-reality simulations of realistic traffic conditions from Hamburg, Germany.http://dx.doi.org/10.1051/matecconf/20168103006
collection DOAJ
language English
format Article
sources DOAJ
author Sommer Matthias
Hähner Jörg
spellingShingle Sommer Matthias
Hähner Jörg
Anticipatory Adaptation of Signalisation Based on Traffic Flow Forecasts within a Self-organised Traffic Control System
MATEC Web of Conferences
author_facet Sommer Matthias
Hähner Jörg
author_sort Sommer Matthias
title Anticipatory Adaptation of Signalisation Based on Traffic Flow Forecasts within a Self-organised Traffic Control System
title_short Anticipatory Adaptation of Signalisation Based on Traffic Flow Forecasts within a Self-organised Traffic Control System
title_full Anticipatory Adaptation of Signalisation Based on Traffic Flow Forecasts within a Self-organised Traffic Control System
title_fullStr Anticipatory Adaptation of Signalisation Based on Traffic Flow Forecasts within a Self-organised Traffic Control System
title_full_unstemmed Anticipatory Adaptation of Signalisation Based on Traffic Flow Forecasts within a Self-organised Traffic Control System
title_sort anticipatory adaptation of signalisation based on traffic flow forecasts within a self-organised traffic control system
publisher EDP Sciences
series MATEC Web of Conferences
issn 2261-236X
publishDate 2016-01-01
description Autonomously adapting signalling strategies to changing traffic demand in urban areas have been frequently used as application scenario for self-adapting systems. Striving for the ability to cope with the dynamic behaviour of traffic and to react appropriately to unforeseen conditions, such solutions dynamically adapt the signalisation to the monitored traffic demands. The Organic Traffic Control (OTC) system is one of the most prominent representatives in this domain. OTC implements a multi-layered observer-/controller architecture. In this paper, we extend OTC’s observer with a time series forecast component to create forecasts of future traffic developments for turning movements. These forecasts are then used to proactively adapt signalisation parameters. We demonstrate the benefit of the developed approach in terms of reduced travel times, and vehicle emissions within near-to-reality simulations of realistic traffic conditions from Hamburg, Germany.
url http://dx.doi.org/10.1051/matecconf/20168103006
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