The objective of the paper is to present a methodology for analysing more realistic networks. The method adopted is the one employed in the existing dynamic assignment models; namely the model consists probabilistic model for the choice of route and departure time and a dynamic adjustment mechanism between network performance and demand which describes the day-to-day evolution of the distribution of traffic in the network. The distinctive feature of the paper is that it proposes two different travel time models which enable the analysis of any network with multiple origin/ destination (O/D) pairs. The first is based on traffic flow theory and determines link travel times as a function of the number of cars in a link at the time of entering the link. The second model is based on queuing theory; delays are assumed to occur at bottlenecks of limited capacity and waiting time is calculated as a function of the queue length at the arrival time at the end of the queue. Numerical simulation experiments are conducted to analyze the impact of changing link capacities and work starting times on the time dependent distribution of departure rates and travel times. The similarity between link flows and travel times obtained from static and dynamic assignment is investigated. Dynamic assignment models provide a truer representation of reality since they are based on more comprehensive assumptions than the static models. It is shown that in highly congested networks the application of static assignment results in travel times which are lower than the ones predicted by the dynamic assignment.(A) This paper is also published in Seminar E (Volume P307) p41- 55. (IRRD 842407).
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