Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen:
Mattsson, Lars-Goeran
Sjoelin, Lina
42nd Congress of the European Regional Science Association: "From Industry to Advanced Services - Perspectives of European Metropolitan Regions", August 27th - 31st, 2002, Dortmund, Germany
Many city authorities consider how to develop long-tem strategies to achieve sustainable transport and land use systems. One of the key issues is the balance between policy measures to increase transport supply and measures to reduce transport demand or to reduce its adverse environmental impact. Some cities grow rapidly. They are often facing increasing congestion problems in their road transport systems. This leads to demand from the citizens or trade and industry for increased road capacity to improve accessibility and to facilitate mobility of people and goods. Such investments alone would not solve the problems, some analysts argue, but would rather induce new car traffic that would keep the congestion more or less at the same level as before. The solution is rather, they claim, to introduce economic instruments such as congestion pricing. Cities are very complex systems. Investments in the road network, or the introduction of congestion pricing, will not only affect the demand for different modes of transport but will also, in the long run, change the location of activities and hence the land use structure of the city. To be able to evaluate such policies appropriately, city and traffic planners need tools that could help them to clarify transport as well as land use effects of different actions. In a long-run perspective they need to be able to analyse the interaction between the transport and land use markets. Will the effects of a policy instrument in the transport market be counteracted or amplified by the relocation of households and workplaces in the land use market? Eliasson and Mattsson (2001) developed a stylised model of a "generic" symmetric city for the simulation of this kind of policies. In the model there are four groups of actors: households, employers, shops and service establish-ments. The households commute to the workplaces and make shopping and service trips by car, public transport or slow mode. In addition, there are road-based goods transport from the workplaces to the shops and service establishments. The different actors locate in the city in response to accessibility factors that are specific to each group of actor. Eliasson and Mattsson (2001) used the model to evaluate transport and land use effects of congestion pricing or a toll ring in the road network. In the present study we extend this analysis to the effects of the introduction of a ring road connecting the innermost suburbs, combined with or without optimal (i.e., marginal cost-based) congestion pricing or a toll ring. The analysis includes the effects on travel time and travel distance by purpose and mode of transport and the effects on the location of households, workplaces, shops and service establishments. A ring road, which is not combined with any economic instrument, will attract activities to the innermost suburbs. Travel by car will increase both in time and distance, while public transport will loose market shares. If the ring road is combined with optimal congestion pricing, this will not change the location pattern very much. The transport effects will be considerable, however. Car traffic volumes will be reduced, and hence congestion and then also car travel times. Part of the car demand will be transferred to public transport and to slow mode that both will increase their shares. If the ring road instead is combined with a toll ring, the location effect depends in an expected way on whether the toll ring is located inside or outside of the ring road. In general, a toll ring has lower car travel reducing effect, and leads to less toll revenues, than an optimal congestion pricing policy. References Eliasson, J. and Mattsson, L.-G. (2001), "Transport and location effects of road pricing: A simulation approach", Journal of Transport Economics and Policy 35: 417-456
Conference Paper

87.25 kB

Publikationen in EconStor sind urheberrechtlich geschützt.