This is centralised reference for all layer types available in the See.Sense Data-Insights Dashboard.
Note: not all layers and features will be available in all dashboard versions.
This shows the number of distinct cyclists travelling through each point. Note that we do not snap to roads, so true desire lines are shown.
Popular routes indicate cyclists perceptions of travel time, facility type, and safety. Use this to examine the ‘desire lines’ where cyclists choose to travel. Consider if cyclists may be avoiding particular areas, or are there roads cyclists may be choosing to avoid rough surfaces or dangerous or congested intersections?
You can also use the AM/PM toggle to see if route popularity changes by morning or evening.
This shows the average speed of cyclists through each point.
Higher average speeds can be indicative of:
However, with higher speeds the chance of an accident as well as its severity increases. Design for speeds that are safe for your community and infrastructure.
You can see if cyclists are flowing or if they’re having to start-stop a lot, fluid movement is indicative of good infrastructure.
The technology in See.Sense lights maps road surface roughness from the experience of the cyclist.
The SSRI scores has been shown to have a high correlation with a visual inspection. See research here conducted by AECOM for more information.
You can use this to identify areas where to prioritise cycle infrastructure maintenance. Areas where there are a high volume of cyclists, or are showing areas where cyclists are experiencing difficulties such as heavy braking, swerving, collisions or where there are reports coming through on the perception report data should be prioritised from a risk management approach.
By improving road surface, you can improve cyclists' comfort and perception of safety, as well as help to reduce accidents.
The See.Sense Road Roughness data can also be used to help inform a Level of Service Analysis. See an example here.
Dwell can time can show you where cyclist flow needs to be improved to make cycling more viable as well as more pleasant.
Higher dwell times can:
Cyclists can swerve or brake suddenly in response to:
You can use this information to identify areas of your network that are causing difficulty to cyclists.
Origin-Destination reveals where cyclists are coming from and and where they are going, as well as where they aren’t going. This is important information for the design of an efficient network that can carry cyclists to areas that meet their needs. It can also help to identify demand for bike parking.
The AM/PM filter will restrict the data displayed to only AM hours or PM hours. This is most useful for separating out commuters going to and from work in the city.