To promote transparency and provide information, the Federal Planning Bureau regularly publishes the methods and results of its works. The publications are organised in different series, such as Outlooks, Working Papers and Planning Papers. Some reports can be consulted here, along with the Short Term Update newsletters that were published until 2015. You can search our publications by theme, publication type, author and year.
The PLANET model, developed by the Federal Planning Bureau within the framework of a cooperation agreement with the Federal Public Service Mobility and Transport, makes it possible to calculate the long-term evolution of transport demand in Belgium. Transport demand includes both passenger and freight transport and is broken down by mode of transport. For rail transport, demand is projected assuming constant average speed on the network over the whole projection period. The PLANET model does not take into account railway infrastructure capacity; in other words, it assumes that the network will be able to cope with any increase in demand without affecting the quality of service. Since the utilisation rate of some lines is already very high, there was a need to extend the scope of analysis of PLANET to estimate the impact of the future railway demand on the network utilisation rate. That analysis, performed at a detailed spatial level (the rail sections), is useful and pertinent, particularly for rail operators and public authorities within the context of the railway investment plans.
Every three years, the Federal Planning Bureau (FPB) carries out long-term projections of the evolution of transport demand in Belgium. The third and latest exercise of its kind, showing the evolution of transport demand over the 2012-2030 period, was published in December 2015. The evolution was cal-culated using the PLANET model.
According to the most recent projection results, the total number of passenger-kilometres travelled over the Belgian territory should increase by 11% between 2012 and 2030 and the total number of tonne-kilometres by 45%. The increase in demand should reach 9% and 62% for passenger and freight rail transport respectively. As a consequence, the share of passenger rail transport should decrease slightly (from 7.9% in 2012 to 7.7% in 2030), while the share of freight rail transport should rise (from 10.4% in 2012 to 11.6% in 2030).
The projected increase in rail transport will inevitably have an impact on the use of rail infrastructure. However, the impact cannot be assessed since the PLANET model does not represent the different transport networks. Moreover, the current rail capacity supply on some sections may prove inadequate to cope with the increase in demand. Identifying these possible capacity bottlenecks could be very help-ful in determining the investment required on the network.
Against this background, we deemed it useful to explore the feasibility of building a bridge between the development in transport demand by 2030 and the capacity of the rail network. The feasibility is analysed along two dimensions: the methodological dimension (can the PLANET model be adapted and if so, how?) and the statistical dimension (are the required data available?).
The results of this two-dimensional analysis led us to assess the impact of the evolution of rail demand on the utilisation level of rail infrastructure. This assessment could be performed at a highly detailed spatial level, i.e. the rail sections instead of lines, since Infrabel and SNCB/NMBS provided very detailed data. More precisely, the additional trains per hour (in both directions) required to meet the increase in demand in 2030 were calculated for every rail section.
The main conclusions of the analysis are:
The developments outlined above are useful and pertinent, particularly for rail companies and public authorities within the context of railway investment plans. However, they are not sufficiently compre-hensive to identify possible saturation problems on the network as the network utilisation level varies considerably with the time of day, especially with regard to passenger transport. Demand is particularly high during peak hours (in the morning and late afternoon). This limitation is not a methodological issue but is due to a lack of pertinent data. If data on the number of trains (and passengers) on the different rail sections by travelling period were available, our analysis could be improved substantially.
Two other opportunities for improvement are worth mentioning. The first one relates to the occupancy rate of passenger trains and the loading rate of freight trains over time. The second applies to the method used to break down geographically the flows of passenger rail transport for other purposes.
Mathematical and Quantitative Methods > Data Collection and Data Estimation Methodology; Computer Programs [C8]
Urban, Rural, and Regional Economics > Transportation Systems [R4]