Generation and Quality Assessment of Route Choice Sets in Public Transport Networks by Means of RP Data Analysis

Generation and Quality Assessment of Route Choice Sets in Public Transport Networks by Means of RP Data Analysis


M Larsen, O Nielsen, C Giacomo Prato, DTU Transport, DK


The paper concerns the generation of choice sets for passengers? route choices in the Greater Copenhagen public transport network. Moreover, the choice set quality is assessed with respect to RP data collected in the Danish Travel Behaviour Survey.


Modelling route choice presumes the generation of a choice set of alternatives that are perceived as available and then are chosen from by travellers. Recent research has posed increasing attention toward the importance of size and composition of choice sets in route choice modelling, and has shown that the generation technique has great impact on route choice model estimates and predictions.
In the literature, limited knowledge is provided concerning the actual route choices of passengers in public transport networks and the evaluation of the quality of generated choice sets with respect to real life choices. One of the reasons lies in the difficulty to collect data on actual route choices in public transport networks, since a lot of information has to be provided to describe the routes actually used by travellers. In fact, while for private transport it is possible to use GPS devices to track routes and then map the data to a physical network, for public transport the same method is of little help because relevant information about the lines used is not retrievable with these devices. A problem with GPS is also that signal fall outs in tunnels (metro and sections of the urban rail system). Moreover, GPS devices do not allow obtaining information on the trip purpose, which is another fundamental piece of information for uncovering route choice determinants. This study relies on approximately 2000 observations of actual route choices in a public transport network, which have been collected by means of a detailed questionnaire gathering all relevant trip information about routes, lines and purposes.
The method for choice set generation in a public transport network is based on a timetable probit-based stochastic transit assignment model based on MSA (Nielsen, 2000 and Nielsen and Frederiksen, 2006). The method defines a doubly stochastic function that accounts for heterogeneity in both perceived costs and individual preferences. Moreover, the method considers similarities across alternatives and differences in feeder modes. The complexity of the route choice of public transport passengers is therefore represented with a high level of detail.
The generated choice sets are tested in terms of quality and number of attractive routes by comparing them with the observed choices. Considering each OD-pair, attractive routes are defined theoretically as alternatives that travellers would consider, and operatively as the set of alternatives actually selected by all travellers sharing that specific OD-pair. Furthermore, the choice probabilities in the generated choice sets are compared to the actual choice probabilities from the route choice observations.
For assessment of the quality of the choice sets, data from the Danish Travel Behaviour Survey are used. This survey collects detailed information about route choices of public transport passengers in the Greater Copenhagen area. The dense public network includes trains (regional, urban, local rail), metro and busses (high class and regular). Most travellers have many possible alternative routes, as a result of the combinatorial nature of the problem of combining different modes and different lines. Because of this combinatorial problem, in this dense public network the number of alternative routes can be very high, even though not all possible routes are relevant and attractive to travellers. Data contain 2000 observations of actual routes for which travellers describe their activities during a specific day and provide details about feeder mode, route (e.g., stations, lines), departure and arrival times, trip purpose, etc.
By using very detailed RP data about public transport route choice, the ability of the generation method to create attractive routes is assessed, the modelled choice probabilities are compared to the actual choice probabilities, and the ability of the method to reproduce actual route choice behaviour is evaluated.

Nielsen, O.A., 2000. A stochastic transit assignment model considering differences in passengers utility functions. Transportation Research Part B, 34(5), 377-402.
Nielsen, O.A., Frederiksen, R.D., 2006. Optimisation of timetable-based, stochastic transit assignment models based on MSA. Annals of Operations Research, 144(1), 263-285.


Association for European Transport