Dynamic User Equilibrium (DUE)

The quantitative analysis of road network traffic performed through static assignment models yields the transport demand-supply equilibrium under the assumption of within-day stationarity. This implies that the relevant variables of the system (i.e. user flows, travel times, costs) are assumed to be constant over time within the reference period. Although static assignment models satisfactorily reproduce congestion effects on traffic flow and cost patterns, they do not allow to represent the variation over time of the demand flows (i.e. around the rush hour) and of the network performances (i.e. in presence of time varying tolls, lane usage, signal plans, link usage permission); most importantly, they cannot reproduce some important dynamic phenomena, such as the formation and dispersion of vehicle queues due to the temporary over-saturation of road sections, and the spillback, that is queues propagation towards upstream roads

KEEPING PASSENGER SURVEYS UP TO DATE: A FUZZY APPROACH

The knowledge of travel demand is an essential prerequisite for analyzing and planning transport supply. Obtaining travel-demand data for a transit system requires passenger surveys that combine counts and interviews. Passenger surveys have two unpleasant characteristics: they are expensive, and the results of such studies tend to lose their validity fairly rapidly. For these reasons, the development of techniques that reduce survey costs and keep demand matrices up to date is gaining increasing interest. Details of a technique for computer-aided processing of passenger surveys are given, and a method for continuous updating of demand matrices is presented. Because traffic surveys represent only a snapshot situation, the proposed updating method employs a fuzzy approach to consider that traffic volumes vary within a certain bandwidth

From transit systems to models: Data representation and collection

This chapter deals with the data that form input and output of passenger route choice models. All information about supply and demand that is relevant to passenger route choice must be captured in a formal way in order to be accessible to mathematical choice models. Over time standard conventions for this formalisation have emerged. In order to avoid repetition in Part III, they are presented once in Sect. 5.1. © Springer International Publishing Switzerland 2016