Economic, Environmental and Social Impacts of Changes in Maintenance Spend on the Scottish Trunk Road Network
3 Transport Scotland road network
3.1 Extent of network
Transport Scotland is responsible for the management and maintenance of the trunk road network in Scotland. The trunk road network comprises route corridors that are considered to be of strategic importance to the economic stability and growth and social wellbeing of Scotland. Data representing the extent, condition and operation of the road network is stored in the Transport Scotland asset database. This has been a primary source of data for this study. A summary of the key data shows:
- 3,007 route kilometres of Motorways and All Purpose Trunk Roads (APTRs);
- 1,891 bridges and 2,614 other structures including 1620 culverts and retaining walls; and
- £17.4 billion asset value, the highest value national asset in Scotland.
Further details on the extent of the network are provided in Appendix A and are summarised in Table 3.1.
Source: Transport Scotland asset database. (NB. Route lengths do not match exactly the lengths given by Scottish Transport Statistics but match the lengths used in the network condition analyses))
3.2 Amount of travel
The trunk road network carries over 35% of all traffic and over 60% of all Heavy Good Vehicle (HGV) traffic in Scotland, whilst being less than 10% of the total length of the Scottish road network.
At the time of analysis, the most recent traffic data (2008) for the Transport Scotland road network, excluding DBFO roads, was extracted from the Transport Scotland asset database. In the asset database, the network is broken into network sections. For each network section, the Annual Average Daily Flow (AADF), for all lanes, was calculated and multiplied by the section length and 365 to derive the annual vehicle km travelled for each vehicle type. The total distance travelled, in 2008, summarised by road type, used in this study is shown in Appendix D. The traffic carried by the trunk road network in 2010, given by Scottish Transport Statistics [1], is shown in Table 3.2. For the 20 years represented in this study (2010 - 2030) the growth in annual distance travelled was assumed to match the growth in the number of vehicles given by the National Road Traffic Forecasts (see Appendix D).
For this study, the traffic data in the asset database was aggregated by:
- Cars = Light vehicles
- LGV = Vans (Rigid 2-axle)
- OGV1 = Rigid 3-axle + Articulated 3-axle
- OGV2 = Rigid 4-axle + Articulated 4, 5 and 6-axle
- PSV = Buses
Note: 1. Scottish Transport Statistics uses the Department for Transport classification of urban and rural roads which is based on population. The classification used here is based on built up/non-built up areas.
Summarising the data by Light and Heavy Goods Vehicles (including PSVs) allowed the percentage of HGVs to be calculated for each road type, shown in Table 3.3.
Travel time information has also been derived from information available from the Transport Scotland website (Transport Scotland, 2006). Two statistics are noted for 2006 (most recent available):
- Additional time spent travelling attributable to congestion was estimated as 9,780,000 hours; and
- Average time lost due to congestion, per vehicle km travelled, was 5.87 seconds.
|
Road Type |
HGV |
|---|---|
|
Motorway |
24% |
|
Dual APTR |
15% |
|
Single APTR |
13% |
Accident data available in the Transport Scotland asset database at the time of the analysis for 2005 [2] to 2010 was analysed. At the time of analysis, only partial data was available for 2010. The analysis focused on determining the number of accidents that occurred under different surface conditions (e.g. wet/damp) and the number of accidents that occurred by the prevailing light condition (e.g. Darkness: No street lighting). The accident data has not been normalised for changes in the level of traffic with time.
Figure 3.1 shows the number of accidents, of all severities, by the prevailing light conditions on all road types. A qualitative assessment of the data in Figure 3.1 showed no clear year on year trend in the number of accidents due to different prevailing light conditions. This is as expected as there have been no significant changes in recent years to the length of the network that is illuminated. Of particular interest is the number of accidents that occur in darkness where the street lights are present and lit. The analysis described in Section 9.4 demonstrates that these accidents are expected to increase if street lighting is turned off, with a corresponding economic impact due to the additional accidents on the network.
Figure 3.1 Numbers of accidents by lighting levels
Figure 3.2 shows the number of accidents by the pavement surface condition recorded at the accident site. A qualitative assessment of this data showed no clear year on year trend in the number of accidents on roads with wet or damp surfaces.
Figure 3.3 shows the number of skidding accidents by the surface condition that was recorded at the accident site. By restricting the data to skidding accidents only it was seen that there has been an overall reduction in the number of 'wet/damp' accidents since 2005, which is consistent with an overall improvement in the network skid resistance shown by the SCRIM data reported in Section 3.5. Further analysis described in Section 7.5 demonstrated the economic impact that budget cuts may have on 'wet/damp' skidding accidents.
Figure 3.2 Number of accidents by road surface condition
3.4 Budgets
Table 3.4 shows the maintenance funding allocations by key activities from 2005/06 to 2010/11.
Each budget head is a summary of a number of work series codes in use by Transport Scotland. These are explained in more detail in Section 6 and are shown in the detailed breakdowns included in Appendix B. The budget heads are self-explanatory, with the exception of the 'Minor Improvements', which includes not only capital but also operating costs to fund the on-going ITS expansion, as well as other investigations, studies and minor projects.
Maintenance funding is a combination of the funding allocated directly to each of the 4 Operating Companies (OCs) used to manage the network and funding directly from head office for items which are most effectively managed on a national basis.
Figure 3.3 Number of skidding accidents by road surface condition
|
Budget Head |
Actual Spend (£m) |
|||||
|---|---|---|---|---|---|---|
|
05/06 |
06/07 |
07/08 |
08/09 |
09/10 |
10/11 |
|
|
Inventory, Inspection and Testing AND Routine and Cyclic Maintenance |
65 |
85 |
79 |
72 |
75 |
69 |
|
Structural Maintenance - carriageway |
39 |
56 |
62 |
43 |
56 |
52 |
|
Structural Maintenance - |
28 |
25 |
22 |
23 |
22 |
25 |
|
Minor Improvements |
26 |
34 |
38 |
34 |
42 |
24 |
|
Miscellaneousn [3] |
3 |
3 |
3 |
4 |
5 |
4 |
|
DBFO Payments |
30 |
35 |
42 |
40 |
38 |
46 |
|
Total |
191 |
238 |
246 |
215 |
238 |
220 |
Past and current pavement condition data (rutting, longitudinal profile variance, skid resistance and residual life) was extracted from the asset database. Both the pavement condition data and the relevant previous budget activity spends (indexed to 2010 prices) have been examined for trends in the variation of each. Comparisons of relevant indicators can give a network level view of the degree to which maintenance has impacted on the pavement asset. This approach has been used in this analysis as part of more detailed investigations.
Figure 3.4 shows the road surfacing budgets and skid resistance. The graph shows that surfacing investment has fluctuated, with generally higher investment levels 5-10 years ago than in the most recent 5 years, and skid resistance has improved over the last 10 years.
Figure 3.4 Skid resistance and road surfacing budgets
Figure 3.5 shows road strengthening budgets, structural condition (represented by pavement residual life), rut depth and ride quality (represented by 3m longitudinal profile variance (LPV)). The graph shows that structural road maintenance investment increased to a peak about 7 years ago, and has since been reducing. Until five years ago, conditions showed improvement but have since either remained constant or deteriorated.
Maintenance scheme data was downloaded from the asset database and aggregated to show the total length of schemes by road type and by treatment type for each of the financial years that scheme data was available. Only those schemes with a valid completion date in the database were included in the analysis to ensure any incomplete or schemes that were not implemented have been excluded. Note that the scheme data used does not include patching works. Scheme data since 2002/03 has been used in this analysis.
Figure 3.6 shows the total length of schemes by road type for each financial year and Figure 3.7 shows the total length of schemes by treatment type for each financial year.
Figure 3.5 Pavement condition and maintenance budgets
Figure 3.6 Total length of schemes by road type and year
Figure 3.7 Total length of schemes by treatment type and year
The number of schemes on each road type (Motorway, dual APTR and single APTR) was also calculated from the same dataset and is shown in Figure 3.8. An analysis of the average (mean) scheme length shows no clear trend, with the average length being between 500m and 900m for all road types and years (Figure 3.9).
Figure 3.8 Number of maintenance schemes by road type and year
Figure 3.9 Average scheme length by road type and financial year