Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/117810
Authors: 
Van Amelsfort, Dirk
Bliemer, Michiel
Year of Publication: 
2005
Series/Report no.: 
45th Congress of the European Regional Science Association: "Land Use and Water Management in a Sustainable Network Society", 23-27 August 2005, Amsterdam, The Netherlands
Abstract: 
We are developing a dynamic modeling framework in which we can evaluate the effects of different road pricing measures on individual choice behavior as well as on a network level. Important parts of this framework are different choice models which forecast the route, departure time and mode choice behavior of travelers under road pricing in the Netherlands. In this paper we discuss the setup of the experiment in detail and present our findings about dealing with uncertainty, travel time and schedule delays in the utility functions. To develop the desired choice models a stated choice experiment was conducted. In this experiment respondents were presented with four alternatives, which can be described as follows: Alternative A: paying for preferred travel conditions. Alternative B: adjust arrival time and pay less. Alternative C: adjust route and pay less. Alternative D: adjust mode to avoid paying charge. The four alternatives differ mainly in price, travel time, time of departure/arrival and mode and are based on the respondents' current morning commute characteristics. The travel time in the experiment is based on the reported (by the respondent) free-flow travel time for the home-to-work trip, and the reported trip length. We calculate the level of travel time, by setting a certain part of the trip length to be in free-flow conditions and calculate a free-flow and congested part of travel time. Adding the free-flow travel time and the congested travel time makes the total minimum travel time for the trip. Minimum travel time, because to this travel time we add an uncertainty margin, creating the maximum travel time. The level of uncertainty we introduced between minimum and maximum travel time was based on the difference between the reported average and free-flow travel time. In simpler words then explained here, we told respondents that the actual travel time for this trip is unknown, but that between the minimum and maximum each travel time has an equal change of occurring. As a consequence of introducing uncertainty in travel time, the arrival time also receives the same margin. Using the data from the experiment we estimated choice models following the schedule delay framework from Vickrey (1969) and Small (1987), assigning penalties to shifts from the preferred time of departure/arrival to earlier or later times. In the models we used the minimum travel time and the expected travel time (average of minimum and maximum). Using the expected travel time incorporates already some of the uncertainty (half) in the attribute travel time, making the uncertainty attribute in the utility function not significant. The parameters values and values-of-time for using the minimum or expected travel time do not differ. Initially, we looked at schedule delays only from an arrival time perspective. Here we also distinguished between schedule delays based on the minimum arrival time and the expected arrival time (average of minimum and maximum). Again, when using expected schedule delays the uncertainty is included in the schedule delays and a separate uncertainty attribute in the utility function is not significant. There is another issue involved when looking at the preferred arrival time of the respondents; there are three cases to take into account: 1.If the minimum and maximum arrival times are both earlier than the preferred arrival time we are certain about a schedule delay early situation (based on minimum or expected schedule delays). 2.If the minimum and maximum arrival times are both later than the preferred arrival time we are certain about a schedule delay late situation (based on minimum or expected schedule delays). 3.The scheduling situation is undetermined when the preferred arrival time is between the minimum and maximum arrival time. In this case we use an expected schedule delay assuming a uniform distribution of arrival times between the minimum and maximum arrival time. Parameter values for both situations are very different and results from the minimum arrival time approach are more in line with expectations. There is a choice to take into account uncertainty in the utility function in either the expected travel time, expected schedule delays or as a separate attribute. In the paper we discuss the effects of different approaches. We extended our models to also include schedule delays based on preferred departure time. In the departure time scheduling components uncertainty is not included. Results show that the depart schedule delay late is significant and substantial, together with significant arrival schedule early and late. Further extension of the model includes taking into account the amount of flexibility in departure and arrival times for each respondent. The results will be included in this paper.
Document Type: 
Conference Paper

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