Rail Modelling ? Integrating Rail with Other Modes
T Worsely, K McNamara, Department for Transport, UK
There is increasing interest in the impact of investment in rail on other modes and on transport emissions. The paper will describe some of the work being undertaken by the UK Department for Transport to improve the quality of its analysis.
The UK Department for Transport (DfT) makes use of two strategic transport models which cover all of the country, the Network Modelling Framework (NMF) and the National Transport Model (NTM) to inform policy and long term transport strategy. There is increasing interest on the part of policy makers in the impact of investment in rail on other modes and on transport emissions and the paper will describe some of the work being undertaken by the DfT to improve the quality of its analysis.
The NMF is time series elasticity based model of rail travel which takes as its base the data on station to station flows derived from ticket sales data. Analysis of time series data at various levels of aggregation has identified the main drivers of demand and the elasticities to forecast demand for rail travel. The model identifies both exogenous effects and the impact of changes in rail service provision, including the effects of crowding on demand. In order to inform policy, the NMF includes modules to estimate the financial costs of providing rail services, changes in the risk of accidents, changes in reliability, rail emissions and the economic costs and benefits of any intervention.
The NTM is a multi-modal 4 stage model which broadly follows conventional modelling practice. It is based on the data on households and their travel choices recorded in the GB National Travel Survey. The model identifies 80 different household types. The limited coverage of this survey makes it impossible to derive a full geographical distribution of trips and the modelling uses the concept of area types, amalgamating the NTS data into 39 different area types.
Because rail trips make up only 2% of all household trips, coverage of rail travel in the NTM is very limited. Moreover, the absence of any geographical information in the NTM limits its use in analysing the impacts of rail schemes on other modes, which is a key requirement when addressing policy concerns about mode choice and transport?s carbon emissions. The Department is working on the integration of the two models and this integration, due for completion in May, will form the basis of the presentation.
The amalgamation of an elasticity based model with a 4-stage one presents a number of issues. The integration of the two models has required the export of rail costs from the more detailed NMF into the NTM?s PASS1 demand module. This has required transformation of the structure of the zones in the different models, moving from the real geography of the NMF into the area type spatial definitions used in the NTM?s demand module. In addition, estimates of station access and egress costs have been added into the NMF trip generalised costs to ensure compatibility with the NTM.
Further work has been required to address the difference between the forecasts provided by an elasticity based single mode rail model and rail forecasts from a multi-modal model. The former tend to result in higher forecasts of rail patronage since income growth has a direct effect on business and leisure travel, with commuting being driven by employment. The main influence on rail growth in the 4 stage model is the increase in the value of time relative to money as income increases leading transport users to shift to longer trips and hence to rail, since these trips show a higher proportion of money costs relative to time than in the case of shorter trips. However, adding these forecasts of rail trips into the 4 stage model violates the model?s assumptions about trip rates and the presentation will cover the options considered for reconciling these differences and ensuring consistency with the overall modelling framework.
Association for European Transport