No matter how sophisticated we get as a society, night time retains its primal effect of making us feel unsafe. We stop feeling comfortable in public places, and we may avoid going outside entirely. Councils know there's a link between street lighting and safety. They’re looking for clearer, more tangible ways to optimise our street lighting and improve safety at night.
Introducing Light Night: a web-based data visualiser for councils and citizens that helps us all make better safety decisions.
Our citizen-facing solution would use council data sets to show the best lit routes on existing wayfinding apps that they already use. Citizens are empowered to choose the route that best serves their needs.
Location data from those apps and other data sets would then help Councils identify lighting success or problem spots in public parks and pavements. They can also measure the effect of new lighting before and after installation. Effective, prioritised lighting installations improves budget spend, emissions output and public safety perception.
A web visualiser for council that tells the story of how lighting affects actual and perceived safety now and over time.
- map interface
- data layers:
- time of day
- lighting source
- transport mode
- crash rates
From preliminary analysis of the Victorian Government Crash Stats extract, we found that if a pedestrian is involved in an accident at night time, the chances of fatality are x3.2 higher when there are no street lights present, so our solution includes this data in the holistic picture.
A 'best lit' route option for citizens in apps they already use to show richer route data than currently available.
- journey planning interface
- alternative 'best lit' route compared to default 'fastest' route
The route would be calculated using Leaflet Route Manager and GraphHopper.
We learnt through user research that citizens mostly use familiar routes at night and do not search out specialised safety information. However they do search for information when navigating unfamiliar environments, so our solution leverages wayfinding apps that the citizen already uses, such as PTV or Strava.
To take this project further, we see potential for:
scaling of data sources to service the entire nation.
additional data sources, such as blue-tooth sniffing, Strava and other location-based APIs
improved data, such as clarification of accident data
functionality such as the ability to select for and compare data across different time periods