Modelling Route Choice Sets in Transportation Networks: Principles and Empirical Validity

Modelling Route Choice Sets in Transportation Networks: Principles and Empirical Validity


P Bovy, TU Delft, NL; O Anker Nielsen, Technical University of Denmark, DK and TU Delft, NL


The paper review route choice sets generation methods for large transportation networks. The two most promising?deterministic constrained enumeration and doubly stochastic path generation are developed and tested on Dutch and Danish cases.


Choice sets of individual travellers play a paramount role in analyzing travel choice behaviour. Choice sets are defined as the collection of travel options perceived available by individual travellers in satisfying their travel demand. From a variety of studies it is well known that the size and composition of choice sets do matter in cases of choice model estimation and demand prediction. Incorrect choice sets (e.g. because of captivity) can lead to misspecification of choice models and to biases in predicted demand levels. While this has been demonstrated for relatively simple choice types such as mode choice, we may assume that it holds as well for the more complex case of route choice. The critical role of choice sets in choice modelling has given rise to profound research into choice set modelling in the transportation field, although largely confined to mode choice. We state that these insights gained on choice set modelling and choice set generation cannot simply be transferred to the route choice realm. For a variety of reasons the specification of route sets for route choice modelling is different and more complex, reason why this topic deserves special attention from researchers and practitioners.

This paper will be devoted to a number topics related to the modelling and generation of route choice sets, specifically for application in large networks including multi-modal networks. The paper above all tries to synthesize existing knowledge on this topic based on a thorough literature review into a single conceptual framework giving ample attention to a theoretical underpinning.

In addition the paper investigates recent new approaches to choice set generation for large networks. The one group of promising approaches is the constrained enumeration procedures. This is often referred to as branch and bound techniques in the research field of road traffic assignment (Prato & Bekhor, 2006) and some adaptations for public transport (Friedrich et al 2001), or as rule-based assignment (in the field of schedule-based assignment, Nuzzolo & Crisalli, 2004). Another promising line of research is combined stochastic (which may include several elements) and deterministic path search. This may include combination with rule-based approaches such as in Nielsen & Frederiksen (2007).

We will first summarize in what respect route choice sets differ from other travel choices implying that some proposed choice set modelling approaches cannot be adopted for routes. Then we will argue that it is necessary and advantageous to distinguish the processes of choice set formation and choice on the part of the traveller. Before going into more detail of choice set modelling, we will discuss the various notions of choice sets and the various purposes for which choice sets may be used. We state that these different purposes, that is supply analysis, model estimation, and demand prediction does matter in choice set modelling. We then present a generic conceptual scheme relating the distinct key elements inherent in each choice set generation approach. This scheme helps in classifying and characterizing the various approaches proposed.

Two approaches will be described in somewhat more detail, namely a deterministic constrained enumeration approach and a doubly stochastic path generation approach. For both of these approaches some indicators for their empirical validity will be presented derived from applications to various uni-modal and multi-modal networks. We exemplify this on two road network cases covering the region around den Haag in Holland and the Copenhagen region in Denmark, and similar two multi-modal public transport cases in the same areas. It is shown, that the new generation of choice set generation models indeed improve the generation of routes compared to prior methods.

Bekhor, S., Ben-Akiva, M.E. and Ramming, M.S. (2001) Route choice: choice set generation and probabilistic choice models. Proceedings 4th TRISTAN Conference, Azores, Portugal.

Friedrich, M. Hofsass, I. & Wekeck, S. (2001). Timetable-based transit assignment using branch and bound. Transportation Research Record 1752, pp. 100-107.

Nielsen, O.A. and Frederiksen, R.D. (2007). Large-scale schedule-based transit assignment ? Further optimisation of the solution algorithm. Chapter 8. Edt. Nuzzolo, A. Forthcoming, Kluwer.

Nuzzolo, A. & Crisalli, U. (2004). The Schedule-based approach ion dynamic transit modelling: a general overview. Schedule-Based Dynamic Transit Modelling ? Theory and Applications. Chapter 1 in book edited by Nigel Wilson and Agostino Nuzzolo. Kluwer Academic. pp. 51-77.

Prato, C.G.. and Bekhor, S. (2006) Applying branch & bound technique to route choice set generation. Paper TRB Annual Meeting, CD-Rom.


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