To help with the planning of intervehicular communication networks, an accurate understanding of traffic behavior and traffic phase transition is required. We calculate intervehicle spacings from empirical data collected in a multilane highway in California, USA. We calculate the correlation coefficients for spacings between vehicles in individual lanes to show that the flows are independent. We determine the first four moments for individual lanes at regular time intervals, namely, the mean, variance, skewness, and kurtosis. We follow the evolution of these moments as the traffic condition changes from the low-density free flow to high-density congestion. We find that the higher moments of intervehicle spacings have a well-defined dependence on the mean value. The variance of the spacing distribution monotonously increases with the mean vehicle spacing.
In contrast, our analysis suggests that the skewness and kurtosis provide one of the most sensitive probes toward the search for the critical points. We find two significant results. First, the kurtosis calculated in different time intervals for different lanes smoothly varies with the skewness. They share the same behavior with the skewness and kurtosis calculated for probability density functions that depend on a single parameter. Second, the skewness and kurtosis as functions of the mean intervehicle spacing show sharp peaks at critical densities expected for transitions between different traffic phases. The data show a considerable scatter near the peak positions, which suggests that the critical behavior may depend on other parameters in addition to the traffic density.