Capacity is a central concept in roadway design and traffic control. Estimation of empirical capacity values in practical circumstances is not a trivial problem; it is very difficult to define capacity in an unambiguous manner. Empirical capacity estimation for uninterrupted roadway sections has been studied. Headways, traffic volumes, speed, and density are traffic data types used to identify four groups of capacity estimation methods. Aspects such as data requirement, location choice, and observation period were investigated for each method. The principles of the different methods and the mathematical derivation of roadway capacity are studied and discussed. Among the methods studied are the headway distribution approaches, the bimodal distribution method, the selected maxima, and the direct probability method. Of the methods based on traffic volume counts, the product limit method is recommended for practical application because of sound underlying theory. An example of the application of this promising method is presented. Attempts to determine the validity of existing roadway capacity estimation methods were disappointing because of the many ambiguities related to the derived capacity values and distributions. A reliable and meaningful estimation of capacity is not yet possible. Lack of a clear definition of the notion of capacity is the main hindrance in understanding what exactly represents the estimated capacity value or distribution in the various methods. If this deficiency is corrected, promising methods for practical use in traffic engineering are the product limit method, the empirical distribution method, and the well-known fundamental diagram method, in that order. The choice of a particular method strongly depends on the available data.

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A simple analysis to derive Branston’s generalized queueing model for (time-) headway distributions is presented. It is assumed that the total headway is the sum of two independent random variables: the empty zone and the free-flowing headway. The parameters of the model can be used to examine various characteristics of both the road (e.g., capacity) and driver-vehicle combinations (e.g., following behavior). Furthermore, the model can be applied to vehicle generation in microscopic simulation models and to safety analysis. To estimate the different parameters in the model, a new estimation method is proposed. This method, which was developed on the basis of Fourier-series analysis, was successfully applied to measurements collected on two-lane rural roads. The method was found to be both computationally less demanding and more robust than traditional parameter techniques procedures, such as maximum likelihood. In addition, the method provides more accurate results. Parameters in the model were examined with the developed estimation method. Estimates of these parameters at a specific period and a specific measurement location were to some extent transferable to other periods and locations. Application of the method to road capacity estimation is discussed.

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Many roundabouts have been built in the Netherlands over the last 15 years. A much-debated issue has been whether to give slow traffic, especially cyclists, priority. Recently, a general recommendation was made: priority for slow traffic inside built-up areas and the reverse for rural roundabouts. Because the implementation of this recommendation could result in a large number of roundabouts with priority for slow traffic, there was a need to develop a method that determined the capacity and delay, taking the influence of slow traffic fully into account. In this study such a model was developed. It is an analytical model that combines parts of existing analytical submodels, with extensions. Motorized traffic entering a roundabout is confronted with three conflicting streams: the well-known circulating stream of vehicles on the roundabout, the parallel slow traffic blocking the entry, and the circulating stream of slow traffic at the next downstream exit that blocks the outgoing motorized vehicles and as a consequence can also block the entry. The model was calibrated successfully with observations from two one-lane saturated roundabouts. With the model not only the capacity per entry can be calculated but also the capacity of the total roundabout, given a relative origin-destination matrix of fast and slow traffic.