Adaptive traffic signal control for real-world scenarios in agent-based transport simulations

Abstract

This study provides an open-source implementation of a decentralized, adaptive signal control algorithm in the agent-based transport simulation MATSim, which is applicable for large-scale real-world scenarios. The implementation is based on the algorithm proposed by Lämmer and Helbing (2008), which had promising results, but was not applicable to real-world scenarios in its published form. The algorithm is extended in this paper to cope with realistic situations like different lanes per signal, small periods of overload, phase combination of non-conflicting traffic, and minimum green times. Impacts and limitations of the adaptive signal control are analyzed for a real-world scenario and compared to a fixed-time and traffic-actuated signal control. It can be shown that delays significantly reduce and queue lengths are lower and more stable than with fixed-time signals. Another finding is that the adaptive signal control behaves like a fixed-time control in overload situations and, therefore, ensures system-wide stability.