Anticipatory Adaptation of Signalisation Based on Traffic Flow Forecasts within a Self-organised Traffic Control System
Organic Computing Group, University of Augsburg, 86150 Augsburg, Germany
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.
© The Authors, published by EDP Sciences, 2016
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