A Large-Scale Agent-Based Traffic Microsimulation Based On Queue Model

We use the so-called queue model introducted by Gawron as the base of the traffic dynamics in our micro-simulation. The queue model describes the links with a flow capacity that limits the number of agents that can leave the link and a space constraint which defines the limit of the number of agents that can be on a link at the same time. Free flow speed is the third key component of traffic dynamics in the model. Flow capacity and space constraint together model physical queues, which can spill back beyond the end of the link. A consequence of this is that fairness between the incoming traffic streams becomes an issue, since in a spill-back situation they cannot be served at their full rate. We implement and verify a simple solution to this; the solution is much simpler than the one chosen in many other models. The traffic micro-simulation is “large-scale” which means the simulation is capable of modeling the behavior of millions of agents simultaneously. We utilize a parallel implementation to speed up the computation. In this implementation, the data is distributed onto a number of computing node, each of which runs a smaller portion of the data. Data distribution and communication among the computing nodes are achieved by freely available software libraries. We test this simulation on two different scenarios using the road network of Switzerland. One of them is aimed to see how the simulation handles the congestion whereas the other one is based on real data of the daily activities of the Swiss people. The parallel version on the bigger scenario gives a runtime that is about 800 times faster than real time on 64 computing nodes using Myrinet. The maximum number of vehicles simultaneously in that simulation is about 160 000.