Traffic flow is a very prominent example of a driven non-equilibrium system. A characteristic phenomenon of traffic dynamics is the spontaneous and abrupt drop of the average velocity on a stretch of road leading to congestion. Such a traffic breakdown corresponds to a boundary-induced phase transition from free flow to congested traffic. In this paper, we study the ability of selected microscopic traffic models to reproduce a traffic breakdown, and we investigate its spatiotemporal dynamics. For our analysis, we use empirical traffic data from stationary loop detectors on a German Autobahn showing a spontaneous breakdown. We then present several methods to assess the results and compare the models with each other. In addition, we will also discuss some important modeling aspects and their impact on the resulting spatiotemporal pattern. The investigation of different downstream boundary conditions, for example, shows that the physical origin of the traffic breakdown may be artificially induced by the setup of the boundaries.
Currently, stationary loop detectors are still the most common source of traffic data. In their simplest form they count the number of passing vehicles and measure their velocity aggregated over intervals of one minute. These values already allow an empirical fundamental diagram of traffic flow to be drawn. A more detailed picture on inter-vehicle dynamics can be obtained if even single vehicle data are available. Knospe al @cite_20 , for instance, used data from loop detectors which also measured time-headways ( the time passing between two vehicles crossing a detector). They analyzed the distribution of time-headways depending on the density and studied the functional relation between speed and distance to the preceding car, known as optimal velocity function. In addition to that, they compared these data to seven traffic cellular automata (CA) models. Knospe al found significant differences between the examined models. In particular, the earlier and simpler models were not able to satisfyingly reproduce the empirical results. More advanced models like the comfortable driving model (CDM), which is one of the models to be studied in this paper, showed good agreement with the empirical data.
@cite_20
2067179438
Based on a detailed microscopic test scenario motivated by recent empirical studies of single-vehicle data, several cellular automaton models for traffic flow are compared. We find three levels of agreement with the empirical data: (1) models that do not reproduce even qualitatively the most important empirical observations, (2) models that are on a macroscopic level in reasonable agreement with the empirics, and (3) models that reproduce the empirical data on a microscopic level as well. Our results are not only relevant for applications, but also shed light on the relevant interactions in traffic flow.