Matsuoka Neuronal Oscillator for Traffic Signal Control Using Agent-based Simulation

Matsuoka neuronal oscillator is proposed to control the traffic signals of an isolated four-phase signalized intersection. The oscillator is a model of central pattern generator (CPG) and has seen various applications in humanoid robots. Matsuoka oscillator was chosen for the traffic signal control because of its stable and predictable rhythmic outputs that exploit autonomously the dynamics of the road system. In this paper, the dynamics of Matsuoka oscillator was described in a set of first-order differential equations and simluated in an agent-based modelling environment. This novel signal control algorithm was validated in a Application Programming Interface (API) function by AIMSUN (Advanced Interactive Microscopic Simulator for Urban and Non-Urban Networks). The results were compared to the performance of the existing traffic system and have shown the potential capability of the proposed algorithm in reductions of vehicle delay time and queues.