The main business objective of KTD as it applies to the road construction use case was to reduce overall costs (e.g. extra hours, travel, parking, ...) and increase the utilization of resources by eliminating unnecessary idle time and time lost in transport between locations.
The main use case we have considered is road construction, but the same model/GUI and logic applies to road maintenance/snow plowing/multi fields farming, etc. Basically, anywhere where field coverage planning is required (think vehicle tracks, different zones, different surface layers) we need to handle first the operations and logistics planning & scheduling in a way that optimizes our KPIs, in particular costs. We needed an APS engine that we can integrate with our software that is handling the in-field execution part at the single vehicle level with autonomous driving simulations to better estimate task duration at any specific geographic zone with specific spatial configuration.
Until recently, KTD was planning manually and using MS Excel. This process was unable to optimize resource usage. It did not scale to growing business activity.
