Vad gäller beträffande Vips? Är användare av Vips övertygade/säkra på att de resultat som Vips ger är&quot;reasonable&quot;. Om dessa användare tycker det kan det ju bero på att de gillar Vips-resultaten bättre än Sampers-resultaten. Vilka empiriska data finns till stöd för att det ena eller andra systemet ger säkrare resultat?
1) bullet 1: Is this really correct? Sampers applies a structured approach first allocating to main modes and then between different lines. 2) bullet 2: For allocating demand between main modes Sampers uses etc...while Vips uses ride times and prices specified per mode and line to generate demand per line and mode 3) bullet 3: Is this not only for CS calculation? If so it should be stated clearly
bullet 1: It seems to me as if the same information about headway and time components is input to bothe systems. The difference lies in the way allocation between modes and lines is carried out; There is no explicit assumption in Sampers/Emme that time tables are not used; what is actually done is that an allocation mechanism is used that under certain circumstances may operate poorly for time table based travel bullet 2: I don't see why this is correct given that I know also price and ride time. I would then choose between different lines at a certain stop incorporating the my GC including time and fare bullet 3: Route =line bullet 4: It does not violate the assumption; rather the approach may be a less satisfactory approximation of behaviour given the assumptions about traveller behaviour
Note that the entire discussion on this slide is based on a) the assumption that a misspecified logit model is applied; there may be other variations of the logit model that are applicable and that also give logsums that are correct estimates b) The discussion here deals with choice between public transport lines; the headline seems to refer to more general situations
This slide seems to imply that Vips gives the correct estimate and that the ratio Samkalk/Vips give a true measure of how much Samkalk overestimates CS for a headway change. However, since Vips is based on the RDT approximation, that we know is not a perfect approximation for long distance travel, there will also be an error in the Vips estimate the magnitude of which we do not know.
6th bullet: Alternative formulation: The logit model that is currently used in Sampers (average time model) gives logsums for combined transport service that may be a less satisfactory approximation 7th bullet: Very definite formulation; consider something milder e.g. &quot;Samkalk calculation of CS may be erroneous when headway is changed&quot;; Are you absolutely shure about the sequencing error? Consider less definite formulation here too.
Transcript
1. <ul><li>TRANSPORTFORUM 2011 </li></ul><ul><li>Towards a model for long distance passenger travel </li></ul><ul><li>in the context of infrastructure and public transport planning </li></ul><ul><li>Summary of work by </li></ul><ul><li>Staffan Algers </li></ul><ul><li>John Bates </li></ul><ul><li>Kjell Jansson </li></ul><ul><li>Harald Lang </li></ul><ul><li>Odd Larsen </li></ul><ul><li>Henrik Swahn </li></ul><ul><li>Financed by Vinnova, Banverket, Sika, SL </li></ul>
2. Reasons for the project <ul><li>It is likely that long distance travel will become more important from a transport policy point of view during the next few decades. </li></ul><ul><li>Both users and researchers in the field have come to the conclusion that the current models have certain deficiencies </li></ul><ul><li>A troublesome problem is that the outcome of an analysis may well differ considerably between different models. </li></ul>
3. Ideal model versus existing models <ul><li>An ideal model should consider individual preferences, also with respect to departure/arrival time and how these interact with time table information. </li></ul><ul><li>It would be useful to try to combine various properties in existing models. There may be different ways to do this. </li></ul><ul><li>Existing models used in Sweden are Sampers, Vips and Visum </li></ul><ul><li>By use of examples and analytical discussions we relate these models to an ideal model, especially for estimates of changes of generalised cost, consumer surplus and demand. </li></ul>
4. Assumptions <ul><li>Assumptions for long distance travellers </li></ul><ul><li>Travellers use timetables </li></ul><ul><li>They “already at home” compare various combinations of lines and modes, with travel time components, prices, departure and arrival time </li></ul><ul><li>Model assumptions </li></ul><ul><li>Travellers minimize generalised cost (G) according to Sampers Vips and Visum. But G varies between individuals in different ways. </li></ul><ul><li>Thus the models deal with different types of random variation </li></ul><ul><li>In Sampers variation wrt taste, measurement errors etc. </li></ul><ul><li>In Vips and Visum variation wrt difference between ideal departure or arrival time and actual times </li></ul>
5. General differences <ul><li>Sampers and Visum generate demand between centroids </li></ul><ul><li>Vips does not generate demand </li></ul>
6. Mapping of routes and modes in the models <ul><li>Sampers deals with “main modes”, while Vips takes into account all combinations of lines and modes </li></ul><ul><li>For allocating demand between main modes Sampers uses the average ride time and average price of the lines in each mode </li></ul><ul><li>Vips specifies separate prices and ride times for lines, implying that the price and ride time for the whole journey, O-D, is the average price and time, weighted with all acceptable combinations (not “main modes”) </li></ul>
7. Sampers – Emme/2 <ul><li>Passengers know the travel time components and headway of all routes; but not the timetable </li></ul><ul><li>Passengers choose only the perceived best stop (one mode) and assigns on routes in proportion to frequency only, without regard for time and fare. (Correct with no knowledge of timetable) </li></ul><ul><li>No distinction between ride times and prices of lines of a mode (e.g. problematic for high-speed rail) </li></ul><ul><li>Violates the assumption that travellers know the timetable and compare times and prices of lines and modes </li></ul>
8. Sampers – Logit model <ul><li>Assigns on ”main modes” with travel time components per mode from Emme/2 </li></ul><ul><li>Exogenous price per main mode in each O-D pair </li></ul><ul><li>Does not take into account combinations of modes </li></ul><ul><li>Does not take into account several airports (e.g. in Stockholm) or several operators </li></ul>
9. The logit model in use and the logsum for public transport <ul><li>Larsen , Lang, Jansson: </li></ul><ul><li>” On combining discrete choice and assignment models” </li></ul><ul><li>HongKong paper December 2010: </li></ul><ul><li>“ long distance models that apply this approach, are miss-specified, leaving us with models that may have biased parameters and unknown properties when used for evaluations of changes in transport systems whether logsums or “rule of the half” (RoH) are applied. The core of the problem is that the implicit random terms of the discrete choice models will not have the assumed properties.” </li></ul>
10. Sampers – Samkalk <ul><li>Consumer surplus is based on change of generalised cost only for the alternative mode that has been subject to change </li></ul><ul><li>For existing/remaining passengers a rectangle </li></ul><ul><li>For new/lost passengers a triangle (rule – of –half). </li></ul><ul><li>Correct if price or ride time is changed </li></ul><ul><li>Not correct if headway is changed </li></ul><ul><li>Headway changes mean that travellers shift between departures, so there is nothing like existing and new travellers </li></ul>
11. Changes of headway M9 (air) and B7 (rail) Headway of M9 is reduced, for ride times, 30 – 90 min . Samkalk produces much larger change of CS
12. Main mode concept - consequences We want to evaluate the effects of introducing high-speed rail between B and C for travellers going from A to C via B. The change in consumer surplus according to Vips is large but zero according to Samkalk. The reason is that Sampers does not take into account the possibility to go by air first between A and B. Since air is not taken into account when rail is subject to change, Samkalk cannot calculate the effect.
13. Main mode problem – Example Luleå-Örebro Vips gave a change in CS by 2 500 and Samkalk by 2 only. Only night train Luleå-Göteborg, via Örebro is taken into account. The combination airline Luleå-Arlanda, Arlanda express train Arlanda-Stockholm plus the rail lines Stockholm-Örebro is not taken into account. Evaluate faster train Stockholm-Örebro
14. Vips and Visum <ul><li>One step for travel paths, lines and modes </li></ul><ul><li>The algorithm in these network models is called RDT – Random Departure Time. Both ideal times compared to actual times and departures are randomly distributed. </li></ul>
15. Conclusions <ul><li>Vips does not generate demand, but Visum does </li></ul><ul><li>Vips does not take into account randomness wrt taste, measurement errors etc. </li></ul><ul><li>Vips has no scientific method for calibration </li></ul><ul><li>Sampers does not take into account randomness wrt departure/arrival time vs actual times </li></ul><ul><li>Emme/2, logit model and Samkalk fails to take into account the assumptions on travellers´ behaviour (known timetables) </li></ul><ul><li>Logit model and logsum in use do not work well for public transport (miss-specified) </li></ul><ul><li>Sampers fails to calculate CS when headway is changed and cannot handle combinations of modes </li></ul>
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