Antifragile Control Systems: The case of an oscillator-based network model of urban road traffic dynamics
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by
Cristian Axenie
2022
Abstract
Urban road traffic continuously evolves under uncertainty. Existing traffic
control systems only possess a local perspective over the multiple scales of
traffic evolution, namely the intersection level, the corridor level, and the
region level respectively. Capturing uncertainty under complex traffic
spatio-temporal interactions is a very difficult problem and we often
experience how fragile such systems are in reality. But luckily, despite its
complex mechanics, traffic is described by various periodic phenomena. Workday
flow distributions in the morning and evening commuting times can be exploited
to make traffic adaptive and robust to disruptions. Additionally, controlling
traffic is also based on a periodic process, choosing the phase of green time
to allocate to opposite directions right of the pass and complementary red time
phase for adjacent directions. In our work, we consider a novel system for road
traffic control based on a network of interacting oscillators. Such a model has
the advantage to capture temporal and spatial interactions of traffic light
phasing as well as the network-level evolution of the traffic macroscopic
features (i.e. flow, density). In this study, we propose a new realization of
the antifragile control framework to control a network of interacting
oscillator-based traffic light models to achieve region-level flow
optimization. We demonstrate that antifragile control can capture the
volatility of the urban road environment and the uncertainty about the
distribution of the disruptions that can occur. We complement our
control-theoretic design and analysis with experiments on a real-world setup
comparatively discussing the benefits of an antifragile design for traffic
control.
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