<aside> 💡 This case study uses Compass custom services.
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Transport authorities maintain complex transport models to understand the current and future state of their network. Particularly with regards to freight and goods/services vehicles, there is currently very little temporal data to inform these models, other than economic data.
Compass IOT was asked to provide, based on specifically identified goods, services and prime move vehicles models, origin-destination outputs to better inform these models.
Traditionally understanding freight movements was done from a mixture of tube counts, and economic and production data. Importantly this data did not explain which routes vehicles take, how long they travel, where they started and ended, and what, if any stops were taken along the way.
To solve the above, Compass IOT was asked to select vehicle makes/models which were either prime movers or goods and services. Compass IOT was to provide an OD matrix based on 79 zones in South Eastern Queensland covering Brisbane, the Gold Coast, Ipswich, Logan, and Sunshine Coast.
The resulting OD pattern looked as below:
Red lines indicate the travel routes of vans, utes, heavy vehicles, and some commercial SUVs from one LGA to another.
The makes and models included in the query included vans, utes, heavy vehicles and some commercial SUVs.
The image below shows the real distance travelled by the mentioned vehicles.
More than 20 million freight trips were recorded in the time period.
Zoomed in image of previous image.
The origin-destination output included: