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Tool Inventory

The Urban Nodes Assessment Tool
The Urban Nodes Assessment Tool

Application Area

  • Data gathering
  • Analysis, scenarios and measure selection
  • Appraisal and assessment

Tool Type

  • Software

Target Audience

  • Large cities
  • Metropolitan regions

Summary

The Urban Nodes Assessment Tool is an Excel template to assess the impact of transport measures on high-level policy objectives related to SUMP (Sustainable Urban Mobility Planning).

The tool takes into account the variety of perspectives of different stakeholders involved in transport network development. Its strength is that it combines two commonly used approaches (MCA, Multi-criteria Analysis and CBA, Cost-Benefit Analysis) to evaluate all of a measure’s impacts (both quantitative and qualitative). Furthermore, it is applicable to hard and soft measures from local to regional level projects.

Input is an initial set of planned or ongoing measures or projects identified by stakeholders to be relevant for the transport network development. With the help of the methodology, an optimal package of measures based on a defined problem and based on high-policy objectives can then be identified.

The methodology was originally developed and tested in the Netherlands to assess the Dutch national transport policies according to their contribution to the improvement of the accessibility of the national road network. Since its inception, the methodology has been developed further for the application in the 88 European urban nodes of the TEN-T core network.

Good Example

The tool has been applied in four urban pilot nodes Helsinki, Genoa, Rotterdam and Ljubljana. For this purpose, local transport planers met in order to assess in advance the likely impacts of potential projects against their contribution to high-level objectives. As a result, projects have been ranked according to their benefits.

Input Data

The tool can either be used with realistic data or with estimated figures based on expert judgement. Fact-based data obviously provides more robust results. Especially monetary data about costs of transport projects are helpful to have.

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