Development and validation of a flexible, open architecture, transportation simulation with an adaptive traffic signal control implementation
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Simulation has been utilized in the planning and development of almost all sectors of the transportation field. The practicing transportation community primarily relies on simulation packages. When a practitioner (or end user) uses a simulation package, most of the simulation development efforts have already been completed. Unfortunately, the use of these simulation packages has several disadvantages, most notably the “black box” phenomenon and reduced modeling flexibility. The simulation model described in this research lays the foundation for a transportation simulation, Open-TS3, that minimizes the black box problem and increases modeling flexibility, while still providing an easy to use package in which highly capable models may be quickly and accurately built. The approach to simulation in this research is to develop a platform that allows for the use of existing constructs where applicable, while still retaining the flexibility for the user to incorporate new basic modeling constructs. Open-TS3 utilizes SIMAN (a simulation language) and ARENA (a simulation development tool), both commonly found in manufacturing applications. In intersection and arterial validation studies, comparing the Open-TS3 to CORSIM, a high level of agreement was seen in the volumes, delays, queues, and speeds simulated by both models. Some differences were seen between the models in overcapacity demand situations, most significantly in left turn operations. Agreement was also seen in a comparison to real-world delays measured for a twelve-intersection downtown Chicago network. The real-world data validation effort also highlighted some important issues regarding validation with real-world data, in particular the difficulties in obtaining data and the potential pitfalls of GPS probe vehicle studies. As a demonstration of the flexibility of Open-TS3 two adaptive signal control strategies are also successfully implemented. The adaptive control strategies are tested on three different networks under varying volume conditions. Based on the Open-TS3 simulations it was seen that adaptive control can provide superior overall performance, but can have a significantly greater range of variability than that of pre-timed control.