Snow removal operations are required to maintain roadway safety during snowy winter conditions. Reliable plans outlining the dispatching of plow trucks must be made to deliver snow removal operations on time and within budget. Historical project performance data can be used to inform and facilitate decision-making processes associated with snow removal operations. This research proposes a data-driven simulation framework for planning snow removal projects considering weather and truck-related data collected by real-time sensors. An in-house developed simulation engine, Simphony.Net, is used to simulate operations based on input information extracted from mined sensor data. This model is capable of simulating plow operations to facilitate planning at both an operational and real-time level. What-if scenarios can be generated to simulate, predict, and optimize project and resource performance. A case study conducted in Alberta, Canada is presented to illustrate the practical application of the proposed method.
|Name||Proceedings - Winter Simulation Conference|
|Conference||2017 Winter Simulation Conference, WSC 2017|
|Period||3/12/17 → 6/12/17|
- Modelling and Simulation
- Computer Science Applications