A multi-agent system for on-line simulations based on real-world traffic data

Abstract

Presents and reviews a framework for online simulations and predictions which are based on the combination of real-world traffic data and a multi-agent traffic flow model. The agent architecture consists of two layers which distinguish the different tasks that road users have to perform. The framework is applied to the urban road network of Duisburg and the freeway network of North Rhine-Westphalia. On the basis of historical data, heuristics are derived, which can be combined with the dynamic data of the simulations to provide a short-term traffic forecast. The necessity for an anticipatory traffic forecast, which includes decision-making and route choice behavior of the road users, is discussed.