Public transport assignment models have increased in complexity in order to describe passengers' route choices as detailed and correctly as possible. Important trends in the development are (1) timetable-based assignment, (2) inclusion of feeder modes, (3) use of stochastic components to describe differences in passengers' preferences within and between purposes and classes (random coefficients), as well as to describe non-explained variation within a utility theory framework, and (4) consideration of capacity problems at coach level, system level and terminal level. In the Copenhagen-Ringsted Model (CRM), such a large-scale transit assignment model was developed and estimated. The Stochastic User Equilibrium problem was solved by the Method of Successive Averages (MSA). However, the model suffered from very large calculation times. The paper focuses on how to optimise transit assignment models based on MSA combined with a generalised utility function. Comparable tests are carried out on a large-scale network. The conclusion is that there is potential of optimising MSA-based methods. Examples of different approaches for this is presented, tested and discussed in the paper.

Delays and restrictions in intersections contribute significantly to the overall travel times in urban traffic networks and therefore also affect route choices. In practice, however, it is quite unusual to include intersection delays in traffic models, logistic models and route guidance systems. Time consuming and tedious data preparation together with the complexity of network updating is the main reason for this, as most transportation software applications can do the necessary calculations. In this paper, we report on the development of a procedure that can automate the task of adding data for intersection delay modelling to an existing network. The method requires a GIS‐based network with link attributes as input data. The method has developed as an extension tool applicable to existing networks and therefore supply of additional data is normally not required. By a set of ‘expert system rules’, the intersections are classified into a number of groups – such as prioritised and signalised intersections, wedges and Y‐junctions – and the required input data for turn delay models is established. The method has been tested on large‐scale networks with good results. Most of the required data was satisfactorily estimated, although some edits had to be made manually. This was mainly the case for roundabouts and for intersections with a very special geometry. In conclusion, the method greatly reduced the burden establishing data sets for intersection delay modelling in urban traffic networks.

Delays and restrictions in intersections contribute signi®cantly to the overall travel times in urban trac networks and therefore also aect route choices. In practice, however, it is quite unusual to include intersection delays in trac models, logistic models and route guidance systems. Time consuming and tedious data preparation together with the complexity of network updating is the main reason for this, as most transportation software applications can do the necessary calculations. In this paper, we report on the development of a procedure that can automate the task of adding data for intersection delay modelling to an existing network. The method requires a GIS-based network with link attributes as input data. The method has developed as an extension tool applicable to existing networks and therefore supply of additional data is normally not required. By a set of`expert system rules', the intersections are classi®ed into a number of groups ± such as prioritised and signalised intersections, wedges and Y-junctions ± and the required input data for turn delay models is established. The method has been tested on large-scale networks with good results. Most of the required data was satisfactorily estimated, although some edits had to be made manually. This was mainly the case for roundabouts and for intersections with a very special geometry. In conclusion, the method greatly reduced the burden establishing data sets for intersection delay modelling in urban trac networks. # 1998 IFORS. Published by Elsevier Science Ltd. All rights reserved.

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Turn-delays in intersections contribute signi®cantly to travel times and thus route choices in urban networks. However, turns are dicult to handle in trac assignment models due to the asymmetric Jacobian in the cost functions. The paper describes a model where turn delays have been included in the solution algorithm of Stochastic User Equilibrium (SUE) trac assignment. When the Jacobian is symmetric, SUE minimises the road users'`perceived travel resistances'. This is a probit-model where the links cost-functions of the links are trac dependent. Hereby, overlapping routes are handled in a consistent way. However, no theoretical proof of convergence has been given if the Jacobian is asymmetric, although convergence can be shown probable for model data representing realistic road-networks. However, according to the authors knowledge SUE with intersection delays have not been tested earlier on a full-scale network. Therefore, an essential part of the paper presents practical tests of convergence. Both geometric delays and delays caused by other turns are considered for each turn. Signalised and non-signalised intersections are handled in dierent ways, as are roundabouts. In signalised intersections a separate model handles queues longer than one green-period. Green-waves can also be taken into consideration. The model has been tested on a large-scale network for Copenhagen with good results. To make it possible to establish the comprehensive data, a GIS-based`expert system' was implemented (see Nielsen, O.A., Frederiksen, R. D. and Simonsen, N. (1997). Using expert system rules to establish data on intersections and turns in road networks.