Data-driven simulation-based model for planning roadway operation and maintenance projects

Emad Mohamed, Parinaz Jafari, Ming Fung Siu, Simaan Abourizk

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

8 Citations (Scopus)


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.
Original languageEnglish
Title of host publication2017 Winter Simulation Conference, WSC 2017
EditorsVictor Chan
Number of pages12
ISBN (Electronic)9781538634288
Publication statusPublished - 4 Jan 2018
Externally publishedYes
Event2017 Winter Simulation Conference, WSC 2017 - Red Rock Casino Resort and Spa, Las Vegas, United States
Duration: 3 Dec 20176 Dec 2017

Publication series

NameProceedings - Winter Simulation Conference
ISSN (Print)0891-7736


Conference2017 Winter Simulation Conference, WSC 2017
Country/TerritoryUnited States
CityLas Vegas

ASJC Scopus subject areas

  • Software
  • Modelling and Simulation
  • Computer Science Applications


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