Several models of route choice in frequency-based assignment are compared for underlying assumptions on service regularity, passenger information, and choice set structure. Numerical results for some simple examples show that route splits differ significantly under different assumptions, so for practical applications the selection of the most suitable choice model is important and none of the models can be regarded as a good approximation for all possible assumptions. Sensitivity of route choice against perturbations of running times or service frequencies is another consideration, because a continuous response improves convergence in demand models with feedback. Finally, it is demonstrated that in terms of expected travel time, the decision about when to alight (and where to continue the journey) is just as important as the decision of which line to board.
We describe a fragment of Allen's full algebra of time interval relations (the algebra of convex relations) that is useful for describing the dynamic behavior of technical systems. After a n intuitive description of the fragment we give two formal definitions and prove that they are equivalent. This provides the basis for the major result of the paper: in a time net in which all interval relations are convex the test for the global consistency of the edge labelling can be canied out in polynomial time (in the general case i t is NP-complete). This result makes convex interval relations a n attractive candidate whereever qualitative reasoning about technical systems requires testing for global instead of local consistency.
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.
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