SWARM PARADIGM IN MODELING TRAFFIC FLOWS ON THE ROAD NETWORK
Abstract
Swarm paradigm is one of the approaches to the task of group control of robots. Its idea is that instead of establishing one control center, the group is considered as a set of equal agents, each of them choosing its behavior on its own, subject to a number of relatively simple rules; but as a result, the desired behavior is synthesized for the group as a whole. This paper deals with application of this approach to modeling the traffic flow of cars on a road network; thus, this sys-tem belongs to the class of micromodels. In the first part of the paper, the mathematical model used is described, the rules of behavior for each car in the traffic – the rules for choosing speeds and the rules for lane changing considering the surrounding cars, based on the traffic rules and the desired goal which is different for different cars, as they enter the simulated crossroad through different roads and want to drive through it in different directions. While the logic of the rules is the same for all cars, particular numerical values of the parameters are randomly generated for each car, providing different behavior ("character") of different agents and different driving styles, from "extremely quiet driving" to "aggressive driving". The second part of the paper pre-sents the software simulator developed by the authors on the base of this model. In the final part, the results of numerical experiments are presented using this simulator for a model crossroad and a real Moscow traffic node at the intersection of the Third Ring Road and Zvenigorodskoye Shosse. The dependence is analyzed of the actual throughput of the traffic node on the intensity of the traffic flow and the ratio of the turning cars to passing straight. As a result of the simulation, realistic dependencies between these values were obtained – in particular, with the increase of the traffic load, the flow initially increases, but then decreases due to the occurrence of traffic jams, which could be visually estimated in the simulator.
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