|کد مقاله||کد نشریه||سال انتشار||مقاله انگلیسی||ترجمه فارسی||نسخه تمام متن|
|250675||502894||2015||11 صفحه PDF||سفارش دهید||دانلود رایگان|
• The paper proposes an analysis of Area C in Milan, Italy, where a charging policy is applied to private vehicles.
• A large number of scenarios with differing demand levels and elasticities by vehicle classes were explored.
• Further data collection included a parallel field survey of changes in PT speed was also undertaken.
• A high degree of correlation between changes in the different measures of congestion and changes in vehicle speed is observed.
• Changes in the total cost of congestion are though more marked than changes in the excess burden of congestion.
The costs of congestion can be measured using three approaches: the total costs, the marginal costs and the ‘excess burden’. Understanding variation in these measures with particular policies is important for planning and resource management. Assessing the cost distribution (e.g. according to priority routes or urban segments) is key to assessing the delivery of both transport objectives and wider social objectives. The aim of this research is to illustrate how the costs of congestion vary with policy-related demand changes around the city of Milan.The case study used is the “Cerchia dei Bastioni” (called for administrative purposes Area C). This is an old urban area within the inner centre of City of Milan network, with a ‘real life’ charging policy that is applied to private vehicles. A large number of scenarios with differing demand levels and elasticities by vehicle classes were explored and equilibrium assignment used to assign demand to the network. Alternative measures for congestion costs were calculated along with other link parameters. Further data collection, including a parallel field survey of changes in PT speed, was also undertaken.The results indicate a high degree of correlation between changes in the different measures of congestion and changes in vehicle speed (at different levels of demand). Changes in the total cost of congestion are, however, more marked than changes in the excess burden of congestion. Sub-optimal conditions appear to exist in certain parts of the network which (it is conjectured) arise as a consequence of the configuration of the network i.e. the presence of one way streets and vehicle restrictions. Identifying a more optimal network is left for further research, as is identifying the precise conditions for which vehicle speeds can be used as a proxy for changes in congestion.
Journal: Case Studies on Transport Policy - Volume 3, Issue 1, March 2015, Pages 44–54