Creative approaches to asset management
I’m a GIS Technician approaching my 4th year in the highways industry and at Yotta. Over the course of this time, I’ve come up with many innovative ways to use GIS to enable customers to manage their assets better.
GIS has an extremely broad reach within the highways industry, from simple creating a visualisation of condition data to complete spatial analysis of multiple datasets to create a clear output (such as Horizons works plans).
Creativity is often associated with more ‘arty’ endeavours, however I firmly believe you can be just as creative with a spreadsheet and two shapefiles as you can be with a canvas and brush.
Grass Verge Cutting
At first glance, you wouldn’t think there’d be much of a link between SCANNER surveys and grass verge inventory. One is an advance machine based survey and the other is an asset that occasionally needs a bit of a trim, but what determines how much of the verge needs trimming? Generally only the 1st 1m of the verge width needs maintaining, however in more rural areas this is insufficient as visibility can be impaired. One solution may be to increase trimming area and frequency on a network-wide level, unfortunately this isn’t the most economical method.
Back to my point of linking SCANNER and verge data. Sufficient visibility is needed across bends and approaching junctions. This can be impaired by an unkempt verge. Mapping and analysing curvature and gradient data collected from SCANNER surveys against grass verge inventory provides a clear visual identification of assets in needs of additional maintenance.
A simple calculation has been performed on gradient of the area of the PMS network section approaching the junction working out the desirable minimum stopping sight distance (as stated in the Design Manual for Roads and Bridges) based off the speed limit and gradient. This is shown in the image below:
The green line instantly shows us that grass verge inventory is present (width data was not available in this instance so aerial imagery was used). The labelling on the black network sections shows the maximum stopping distance based on speed limit, and the labelling on the red gradient lines shows the actual stopping distance based on speed limit and gradient. So for 150m approaching the junction, any grass verge >1m wide would need additional maintenance (light red polygon). Additionally, this method can also be used to discount any verges not in need of additional maintenance, reducing money spent on grass cutting.
A New Skid Resistance Surveys Approach
The standard approach to implementation of Skid resistance surveys site categories are based on HD 28/15 (DESIGN MANUAL FOR ROADS AND BRIDGES, V7, S3). This guidance permits multiple investigatory levels per site category. I created a method ‘expanding’ these site categories to only allow one investigatory level per category. E.g previously an R site category (Roundabouts), was one category with either an IL of 0.45 or 0.50 depending on risk. Expanding these instead creates two distinct categories; one for standard roundabout sites and another for higher risk areas. This method is not just advantageous for the analysis of Skid resistance surveys data, the high risk areas of the carriageway asset can also be immediately and easily identified to manage safety of the carriageway asset independent of Skid resistance surveys’ data. An example of a select few can be seen below:
These are both a small sample of some of the exciting, innovative projects I have worked on at Yotta. I firmly believe the positive atmosphere and technological freedom given to staff contributed to my creative use of data, and I look forward to developing and applying this more in the future.