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Discusses the detail of developing and updating the National Transport Model version 2 to a base year of 2015.
Outlines the steps taken to recalibrate the updated National Transport Model.
Explores options for maintaining robust values of travel time savings over time.
Investigates the treatment of non-recoverable VAT on scheme costs in appraisal.
Review of the rail demand forecasting methods used by government, the study was completed in 2 phases.
Review and analysis of changing travel patterns among people aged 17-29.
Explains why and how DfT appraises transport investments and presents the department's latest related technical research and future plans.
Provides recommendations on the use of mobile network data in transport modelling.
Research producing updated emissions curves for use in WebTAG and the National Transport Model, including CO2, NOx and PM10.
Development work relating to the National Travel Survey.
Tool to search questions asked in main transport surveys conducted since 2000, including user guide and background information.
Study of the links between appraisal and evaluation of transport schemes and how these links can be improved.
Investigation into the benefits to transport from better data sharing, the case study took place in the Cambridgeshire A14 corridor.
A formal audit and peer review of research undertaken to derive values of travel time savings and reliability.
Qualitative study focusing on business travel decisions and how businesses value travel time.
Reports from a study conducted to recommend up-to-date national average values of travel time.
Review of the distributional impact (DI) appraisals evidence base to ensure it remains relevant and proportionate for transport schemes.
Investigates people’s attitudes to the importance of the strategic rail network and how this varies among people of different gender, age and working status.
Sets out evidence of road traffic trends and the factors driving them.
Investigated estimates made in literature on how road traffic changes in response to changes of population growth, income growth and fuel cost.
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