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A speed threshold is a crucial parameter in breakdown and capacitydistribution analysis as it defines the boundary between free-flow andcongested regimes. However, literature on approaches to establishing thebreakpoint value for detecting breakdown events is limited. Most of existingstudies rely on the use of either visual observation or predefined thresholds.These approaches may not be reliable considering the variations associated withfield data. Thus, this study compared the performance of two data-drivenmethods, that is, logistic function (LGF) and two-regime models, used toestablish the breakpoint from traffic flow variables. The two models werecalibrated using urban freeway traffic data. The models'performance resultsrevealed that with less computation efforts, the LGF has slightly betterprediction accuracy than the two-regime model. Although the two-regime modelhad relatively lower performance, it can be useful in identifying thetransitional state.

A Comparative Study of Parametric Regression Models to Detect Breakpoint in Traffic Fundamental Diagram