A High-Resolution Cellular Automata Traffic Simulation Model with Application in a Freeway Traffic Information System

Abstract

In this article, we describe a novel traffic information system for the freeway traffic in North Rhine‐Westphalia (NRW), the most populous German state. It consists of more than 4,000 loop detectors, a simulator, and a microscopic and macroscopic graphical interface. These should be considered as “data input,”“data processing,” and “data output,” respectively. First, we discuss the loop detectors: Their mode of operation, how and where they are located, and the quality of their measurements. Next, we describe the simulator, especially its high‐resolution cellular automaton model of traffic flows, the abstraction of the road network into tracks and nodes, how the data from the loop detectors is integrated, and we give some details on an efficient implementation of the dynamics. Finally, we discuss the graphical interfaces, which display the simulated traffic states, and we give some concluding remarks. In particular, we present the traffic information web page http://www.autobahn.nrw.de, where the simulated actual traffic state on the freeway network in NRW can be sighted.

Itsumo

“…At a macroscopic level, the visualization considers only data which reflect the overall behavior of the network, providing an useful tool to capture the big picture of what is happening in a specific scenario. It is useful to provide this kind of information via the internet, as it has been the case in [2]. The microscopic level provides an interface through which one can see, both in 2D and 3D manner, individual vehicles movement.…”

Cellular Automaton Model with Dynamical 2D Speed-Gap Relation

“…BLM is one of the most popular models. It has been used by Hafstein et al (2004) to simulate traffic flow on the autobahn network in North Rhine-Westphalia; by Mallikarjuna and Rao (2009) to study heterogeneous traffic observed in developing countries; by Appert-Rolland and Du Boisberranger (2011) to test lane changing rules; by Meng and Weng (2011) to simulate the heterogeneous traffic in work zones; and by Knorr and Schreckenberg (2012) to analyze the strategy to reduce traffic congestion with the help of vehicle-to-vehicle communication. However, BLM has been criticized by KTPT.…”

Evolutionary Computation Applied to Urban Traffic Optimization

“…The main results are that the provision of dynamic route guidance can simultaneously benefit the individual performance of drivers, both guided and unguided, as well as the system performance of existing transportation infrastructure. In (Hafstein, S. F., et al, 2004) a high resolution cellular automata freeway traffic simulation model applied to a Traffic Information System. They provide a simulation for current traffic zones without loop detectors, and 30 min.…”