Will it be possible to achieve a both simpler and better fare structure? Case study Oslo ANGELL, Truls; JANSSON, Kjell WILL IT BE POSSIBLE TO ACHIEVE A SIMPLER AND EFFICIENT FARE STRUCTURE? – CASE STUDY OSLO * Truls Angell, Ruter AS, Oslo, Norway Kjell Jansson, Møreforsking Molde AS, Norway ABSTRACT In many cities in the world zone systems are used for public transport fares. Such systems may very well approximately accord with economically efficient pricing. The reason is that zones can vary with size and location so that prices can approximately reflect the social marginal costs of journeys. We believe, however, that many cities use an excessively large number of zones, which is not necessary and complicated for the passengers. In this paper we hope to be able to demonstrate that such a complicated zone systems can be substantially simplified while maintaining or even improving economic efficiency. We will describes how the zone fare structure in the city of Oslo can be improved, but also implementation difficulties including conflicting distribution issues etc. in the political process, The political aim is now to introduce the new system early in 2011. The basis for this paper is a work financed by Ruter AS, the public transport authority in the Oslo region (Oslo and Akershus), Norway. The result of the work is found in Ruter As (2008) and Jansson (2008). Keywords: fare structure, zone system, efficiency, integration, simplification, distribution, political process 1 INTRODUCTION The Oslo region comprises Akershus fylke (County), including the city of Oslo. The present fare structure is different for Akershus outside Oslo and for the city of Oslo respectively. The city of Oslo has had a flat fare for over 35 years. In Akershus outside Oslo there are in total 88 different zones and the number of zone passages for all routes in both directions are 2 242. This system has been regarded as too complicated. Besides zoning, also the present fare structure is fairly complex. Until 2008 the Oslo region had two responsible public transport authorities, Oslo Sporveier for the city of Oslo and SL for Akershus outside Oslo. Then a common authority, Ruter, was established. Among other things it was then considered necessary to renovate the fare system, including better integration and simplification. The objectives of a new structure were to achieve a common fare structure for the whole of the Akershus region, which is simpler and more understandable than the present one. Section 2 describes the basis for the Oslo study. Section 3 includes a brief description of various discussed fare systems and the analysis of the proposed fare system. Section 4 summarizes principles for efficient pricing. Section 5 describes the political process and * This paper was financed by Møreforsking Molde AS, Norway and Ruter AS, Oslo, Norway 12th WCTR, July 11-15, 2010 – Lisbon, Portugal 1 Will it be possible to achieve a both simpler and better fare structure? Case study Oslo ANGELL, Truls; JANSSON, Kjell implementation issues and the main conclusions are drawn in section 6. The appendix includes a brief description of the computerized network model that was used. 2 BASIS FOR THE OSLO CASE STUDY 2.1 Study area, route network, revenues and costs The area comprises the region (fylke) Akershus, which includes the city of Oslo. The area is approximately 5 014 square km, of which only 250 square km in urban areas, half of which within the city of Oslo. See the map below. Figure 1 - The area studied . 12th WCTR, July 11-15, 2010 – Lisbon, Portugal 2 Will it be possible to achieve a both simpler and better fare structure? Case study Oslo ANGELL, Truls; JANSSON, Kjell The region is served by 450 bus routes, 6 tram routes and 5 metro routes, operated by the authority Ruter. The number of vehicle kilometers available to passengers per year is around 73 millions. The region is also served by trains operated by the national state railways (NSB). All these train services have their start or end terminals far out of Oslo centre but they stop at the main railway station in Oslo and at a number of other stops within the Ruter area. Ruter has an agreement with NSB, which allows the passengers in the region to use the train services at the prices determined by Ruter, for which Ruter remunerates NSB. All monetary figures in the paper are expressed in Norwegian kronor (NOK). 1 € is approximately 7.8 NOK (June 2010). The total revenue in 2009 was around NOK 2 000 million and the total cost around NOK 3 500 million. 2.2 Purpose and objectives of the study A number of fare structure alternatives were analyzed. The objectives of a new structure were to achieve: A simpler and more understandable structure, A common fare structure for the whole of the Akershus region, A minimum loss of passengers or revenues, An increase or only a small loss of socio-economic efficiency, A politically acceptable redistribution profile. With several objectives inevitably conflicts will occur. In this study one objective was also to try to minimise such conflicts. The commercial objective means to achieve unchanged (or more) passengers with higher (or slightly lower) revenues. In order to measure the commercial objective we employ an index. The index is the number of trips multiplied with the revenues, which is defined as 1 for the present situation. If this index is for example 0.998 for a fare structure alternative, it means that the alternative is 0.2 per cent below the present level. In other words, one could achieve the same number of trips with 99.8 per cent of the revenues, or the same revenues with 99.8 per cent of the trips, or a combination with somewhat higher revenues and somewhat fewer trips. To achieve the same or more revenues with fewer zones is of course simple; it just means to raise the fares. However, in order to lose a minimum number of passengers at the same time, one must raise the fares in submarkets with relatively low price elasticity and maybe reduce the fares in submarkets with relatively high price elasticity, the well-know Ramsey pricing principle. Empirical evidence suggests that price elasticity is lower for periodical travel cards (e.g., monthly passes, mostly used for peak travelling) and lower for short trips, especially to the city centre, than for long regional trips, since the car alternative is less attractive for short trips due to relatively high fixed costs such as parking costs. Finally price elasticity grows with the price itself. 12th WCTR, July 11-15, 2010 – Lisbon, Portugal 3 Will it be possible to achieve a both simpler and better fare structure? Case study Oslo ANGELL, Truls; JANSSON, Kjell Socio-economic efficient pricing means that the prices should reflect the marginal costs for passengers and the operator. This means that the prices should be higher when and where demand is high and capacity is exhausted. The passengers suffer from longer boarding times and in-vehicle congestion and the operator´s cost increases with boarding times, at least for bus service. In practice this typically means that the prices should be higher closer to the city centre where the capacity use (load factor) is higher. A fare zone system should thus have successively smaller zones when moving from the periphery to the city centre. That prices are higher per distance unit close to the city centre thus accords with both commercial objectives and socio-economic efficiency. See some more details in section 4. A politically acceptable redistribution profile may mean that some passengers may not suffer from “too high” price increases. In this case the political aim was not to harm travelers within the city of Oslo too much. 2.3 Method employed Basically the network model Vips 1 calculated public transport travel time components and price in each O-D pair. On this basis and with car travel times calculated by the Emme/2 network model, the regional transport model RTM23 (see Rekdal et al. (2008 )) produced travel matrices for peak and off-peak for the purposes work, school, other. Since the fare systems today are different in Oslo and the remainder of the county Akershus, the final matrices were, for peak and off-peak respectively, all in all 8 matrices 2: For peak and off-peak respectively: Oslo – travel card Oslo – single ticket Akershus, except Oslo – travel card Akershus, except Oslo – single ticket For all simulations of effects of various zone structures, fare structures and fare levels the network model Vips was again employed. This model simultaneously deals with all routes and modes. Fares are specified per route, where all routes have zone fares. The model can apply different (convenience) ride time weights for each mode. After calibration the weights chosen were 1.05 for bus, 1.0 for tram, metro and boat, and 0.85 for train. Basic principles of the Vips model is fund in the appendix. For the alternative fare systems only four matrices were needed since Oslo and Akershus should have the same fare structure. 2.4 Present zones and fare levels The map in figure 2 below shows the present zone system. It consists of “rings” around Oslo centre, where each ring has a width of around 6 km. There are maximum 18 rings, but since 1 The Vips model is no longer maintained but the basic algorithms are implemented in the network model Visum. 2 In practice there is a number of fares within each of these categories, but we had to simplify to make the work manageable. 12th WCTR, July 11-15, 2010 – Lisbon, Portugal 4 Will it be possible to achieve a both simpler and better fare structure? Case study Oslo ANGELL, Truls; JANSSON, Kjell each ring is divided in sectors there are in total 88 different zones.