ArcGIS Velocity & Live Waze Data


The Waze for Cities program provides Local Government Authorities and Transport departments access to real-time, anonymous incident and slow-down information direct from drivers. It is a free, two-way data exchange partnership, empowering the public sector with improved situational awareness, comminucation with drivers and assists with infrastructure planning.

ArcGIS Velocity allows you to ingest the Waze feed and use if for incident detection, response and pattern analysis workflows.

Some examples of how this feed could be used:

  • Generate customer request for reported potholes, abandoned cars and illegal dumping.
  • Weekly ‘Top 5’ traffic hotspot areas in your Local Government Area
  • Road closure alerts – this feed from Waze was used during/after the 2019/20 bushfires
  • Level crossing removal – how has the traffic changed before/during/after these projects
  • Notifcations if crashes are reported near vital facilities
Using batch analytic in Velocity to create a scheduled ‘Waze Rate’ on a road network

The workflow in the video may provide some ideas on how ArcGIS Velocity could be used for getting more out of the Waze feed, or from similar datasets such as pedestrian counters, bicycle counters, parking sensors, crash statistics and your work order system feeds.

ArcGIS Velocity enables you to consider a Lamda architecture to processing your data.

ArcGIS Velocity lets you perform real-time analytics to keep data streaming in, and batch analytics to process larger chunks of the data at once. The outputs of these are then served to the portal for downstream apps to leverage.
Real time analytic fetches the Waze incidents and persists them to a spatiotemporal layer, in this case with no processing.
Big Data Analytic is run daily to pre-compute valuable information products, which can be discovered and shared in the ArcGIS Online portal.
Find Hot Spots dentifies statistically significant hot spots and cold spots in the Waze data
The Snap to Network takes advantage of road attributes for driving direction in conjunction with the bearing value recorded in the Waze data. This allows for more accurate snapping of Waze incidents to the road network.
Snapping the data to the correct side of the road, and performing a spatial join and calculating the rate of incidents along each road segment (using its length) allows for a better understanding of the incidents across the road network
Using the greyscale + invert effects on the State VicMap basemap, along with the bloom layer effect on the Waze Rate layer to make it pop out a bit.

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