Antifragile Control Systems: The case of an oscillator-based network model of urban road traffic dynamics

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.