Qualitative Change of Car-Following Behavior Observed in Real Traffic
Microscopic dynamical properties of traffic flow are studied from the aspects of vehicle behavior and driver operation. We studied the nature of fluctuations around the critical region in real traffic by analyzing a time series of variations of velocity o
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Summary. Microscopic dynamical properties of traffic flow are studied from the aspects of vehicle behavior and driver operation. We studied the nature of fluctuations around the critical region in real traffic by analyzing a time series of variations of velocity obtained from single-vehicle data measurement. We found that the probability density function calculated from the time series of velocity variations is transformed, while a Gaussian distribution transitions into a stable symmetrical L´evy distribution. The power-law tail in the L´evy distribution indicated that the time series of velocity variation exhibits critical fluctuations. The power-law tail in the probability density function suggests that dynamical processes of vehicular traffic are related to a time-discrete stochastic process driven by random amplification with additive external noise. In contrast, the empirical data of deceleration in a carfollowing situation obtained from the driving simulator experiment indicated a large dispersion of perceptual quantities of a driver when operating the brake pedal. The result suggests that the algorithm for operating the brake pedal is closely related to the random amplification in the discrete stochastic process.
1 Introduction The phase transition of vehicular traffic is a universal feature of traffic flow [1–3]. One of the empirical facts characterizing the dynamical process in the phase transition of vehicular traffic is given by the metastable branch derived from the flux-density relation (i.e., the fundamental diagram), where spontaneous formation of high-density flow and its decay are observed in measurement of variations of flux with density. In this relation, flux increases in proportion to density under the critical point. However, a discontinuous reduction of flux occurs beyond the critical point, and jams eventually emerge through a mixed state of freely flowing traffic and jams (e.g., stop-and-go traffic). In typical measurements of traffic using roadside detectors, the assumption of constant velocity and the following distance of individual vehicles on a stretch of road, which is divided by sensors, restricts the resolving power
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Yasushi Yokoya, Yoichi Asano, and Nobuyuki Uchida
of data collection [2–5]. The restriction hinder the direct comparison of empirical data on real traffic and the results of the numerical simulations or the analytical calculations especially in the critical-density region with strong fluctuations of velocity [6]. Therefore, it is important to interpret the fluxdensity relation given by empirical data of the time series of the velocity and the headway of individual vehicles. In this paper, microscopic dynamical properties of traffic flow are studied from the aspects of both vehicle behavior and human driver operation. The real-time behavior of a vehicle in real traffic is measured by an onboard apparatus. The analysis based on single-vehicle data potentially enables us to analyze the relation between the microscopic processes in the various dynamical phases and the whole surrounding situation (e.g., en
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