No abstract

The traffic flow analysis and the relevant vehicle distribution ("free-moving" or "platooned" vehicles) IntroductionThe traffic flow composition and the relevant presence of vehicle platoons is particularly interesting in traffic study, and more generally in Highway Engineering, with reference to a plethora of theoretical and practical applications. For instance, as for "traffic operations" [1][2][3][4], it is well known how the presence of platoons can influence breakdown probability [5,6]. Moreover, platoon analyses turned out to be important also in the study of car accidents and road safety [7]. Such a very high practical interest accounts for the numerous models developed over the years. By way of an example, it is worth mentioning the research conducted by Baras et al. [8], which also considers facilities with interrupted flow -and the most recent studies by Ramezani et al. [9] and Jiang et al. [10]. Still today, therefore, the topic has a remarkable scientific and practical interest and deserves in-depth analysis.At first, this article briefly describes the Pearson type III distribution which represents a time headway probability model (more specifically, a generalized mathematical model). The peculiarity of the Pearson type III distribution is its capacity to generate distribution families depending on the chosen model parameters, which can be suited to a plethora of types of traffic phenomena. In the course of this research, some of the above formulations were used to analyse a vehicle distribution within a traffic flow in steady-state conditions and notably to identify the presence and composition of vehicle platoons. In order to apply this analysis to a great number of observations, a specific algorithm was designed and calibrated according to empirical surveys, suitable to randomly simulate a traffic flow and to "identify" the essential characteristics of any present vehicle platoon. The algorithm was implemented to generate realizations of the random function Q(t) (i.e. a traffic flow on a road cross-section in function of time t) starting from input data. The resulting random functions were properly studied and their main characteristics (i.e. non-random functions: mathematical hope and variance) were determined to confirm the steady state flow hypothesis assumed for the development of this study.

Vehicular time headway is an important parameter which characterises traffic flows and a great number of Road Engineering applications utilise time headway statistical models (for example the distribution of time headways contributes to the determination of the capacity, delay and queue at intersection). In this paper two dichotomic laws are presented: the log-normal shifted negative exponential distribution (ENTLN) and the Pearson's type III shifted negative exponential distribution (ENTPIII). These distributions can be useful in studying partially conditioned flows. A complete method for the calibration of these models is then given and is an alternative to the method of moments. Finally, a comparative analysis is made between the two models proposed and others available in literature on the basis of a common significant set of measured time headways.

This paper deals with the problem of model identification, calibration and validation for traffic countings on two-lane rural highways. A criterion for preliminary selection of arrival laws as a function of appropriate sample statistics and a technique for deciding whether sample data sets of traffic counting are congruent with stationary time series behavior are suggested; besides arrival laws currently used in research and engineering practice, the Neyman distribution has been also applied although it is not frequently implemented in the field of traffic engineering. Moreover, this work aims at applying these methods to a set of empirical data derived from a recent survey on two two-lane rural highways; the arrival laws that best agree with the observations are found and the relations between the parameters identifying the arrival laws and the flow rates are worked out. Finally, the results have been compared to those achieved in similar observations, carried out by one of the authors in the past.