Highway Authority Network Classification System
From Wiki
(Created page with 'Comparing crash rates between highway authorities can be misleading due to the variation in road characteristics across the country. For example, it is unlikely that comparing th…') |
|||
| Line 1: | Line 1: | ||
| - | Comparing crash rates between highway authorities can be misleading due to the variation in road characteristics across the country. For example, it is unlikely that comparing the crash rate in central London to the crash rate in the Shetland Islands will provide a meaningful assessment of performance. In order to address this issue, Road Safety Analysis have devised a classification system which groups similar authorities together so that meaningful comparisons can be made. | + | Comparing crash rates between highway authorities can be misleading due to the variation in road characteristics across the country. For example, it is unlikely that comparing the crash rate in central London to the crash rate in the Shetland Islands will provide a meaningful assessment of performance. In order to address this issue, Road Safety Analysis have devised a classification system which groups similar authorities together so that meaningful comparisons can be made. From January 2014 the [[RSA Highway Authority Network Classification System]] dimension is included in MAST. |
The classification system is based on ‘Network Density’ which is calculated by dividing the total length of roads (km) in a highway authority by the area (km²) of the highway authority. This ‘Network Density’ value gives an indication of how urban an authority is and authorities with similar network density values tend to have similar crash rates. When plotting the crash rate index values against the network density values a correlation was evident with road risk generally increasing as the network density increased. Percentage of urban roads in an authority, as [https://www.gov.uk/government/statistical-data-sets/rdl02-road-lengths-kms defined] by the [[Department for Transport]], are also used in the classification system. Grouping highway authorities using the ‘network density’ and ‘percentage urban roads’ figures led to the creation of 5 super-groups and 11 sub-groups. The parameters for these are shown in the following table: | The classification system is based on ‘Network Density’ which is calculated by dividing the total length of roads (km) in a highway authority by the area (km²) of the highway authority. This ‘Network Density’ value gives an indication of how urban an authority is and authorities with similar network density values tend to have similar crash rates. When plotting the crash rate index values against the network density values a correlation was evident with road risk generally increasing as the network density increased. Percentage of urban roads in an authority, as [https://www.gov.uk/government/statistical-data-sets/rdl02-road-lengths-kms defined] by the [[Department for Transport]], are also used in the classification system. Grouping highway authorities using the ‘network density’ and ‘percentage urban roads’ figures led to the creation of 5 super-groups and 11 sub-groups. The parameters for these are shown in the following table: | ||
Revision as of 10:32, 15 January 2014
Comparing crash rates between highway authorities can be misleading due to the variation in road characteristics across the country. For example, it is unlikely that comparing the crash rate in central London to the crash rate in the Shetland Islands will provide a meaningful assessment of performance. In order to address this issue, Road Safety Analysis have devised a classification system which groups similar authorities together so that meaningful comparisons can be made. From January 2014 the RSA Highway Authority Network Classification System dimension is included in MAST.
The classification system is based on ‘Network Density’ which is calculated by dividing the total length of roads (km) in a highway authority by the area (km²) of the highway authority. This ‘Network Density’ value gives an indication of how urban an authority is and authorities with similar network density values tend to have similar crash rates. When plotting the crash rate index values against the network density values a correlation was evident with road risk generally increasing as the network density increased. Percentage of urban roads in an authority, as defined by the Department for Transport, are also used in the classification system. Grouping highway authorities using the ‘network density’ and ‘percentage urban roads’ figures led to the creation of 5 super-groups and 11 sub-groups. The parameters for these are shown in the following table:
| Sub-Group | Sub-Group Description | Super-Group | Network Density Range | Urban Road Range |
|---|---|---|---|---|
| A1 | Very densely networked, super urban London Boroughs | A | 16+ | 97+ |
| B2 | Very densely networked super urban authorities not in London | B | 16+ | 90-99 |
| B3 | Fairly densely networked, very urban authorities | B | 10-15.99 | 90+ |
| C4 | Fairly densely networked fairly urban authorities | C | 10-15.99 | 70-89 |
| C5 | Less densely networked urban authorities | C | 5-9.99 | 70-99 |
| C6 | Less densely networked mixed rurality authorities | C | 5-9.99 | 40-69 |
| D7 | Sparsely networked mixed rurality authorities | D | 2-4.99 | 40-89 |
| D8 | Sparsely networked rural authorities | D | 2-4.99 | 20-39 |
| D9 | Sparsely networked very rural authorities | D | 2-4.99 | 0-19 |
| E10 | Very Sparsely networked mixed rurality authorities | E | 0-1.99 | 0-39 |
| E11 | Very Sparsely networked very rural Scottish Islands | E | 0-1.99 | 0-19 |
| Z99 | Not classified | Z | N/A | N/A |
