A BIM-Integrated Agent-Based Simulation Method for Time-Space Conflict Detection Among Mobile Resources in Construction Projects

Date

2024-9-05

Author

Khataei, Saman

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

170
views

185
downloads

Cite This

Schedule compression techniques are frequently used to meet the construction projects' temporal deadlines. Crashing is a common technique in this regard and requires an increase in the number of resources of the critical path activities to shorten the duration of work. However, any increase in the project resources will increase the interactions among them, leading to time-space conflicts that should be taken into account during crashing analysis. Conventionally, the crashing analysis is performed subjectively, relying on the project planner’s insights or previous project records, which may not lead to reliable estimations. To achieve a more accurate estimation for crashing alternatives, space congestion among the resources should be quantified and involved in the analysis with a project-based and quantitative approach. This study presents a novel method for generating and evaluating the crashing alternatives that are laid on the agent-based simulation (ABS) and BIM model. The method aims to increase the construction simulation fidelity and fulfill some of the current gaps by quantifying time-space conflicts to support the time-cost trade-off and corresponding risk analyses. The method takes a 4D BIM model, an agent pool, and crashing alternatives as input sets and generates a simulation, in which the agents represent project manpower and machinery resources (crews) that can act independently on the basis of predefined behavioral patterns and move according to an artificial intelligence (AI) pathfinding algorithm supported by their perception of the environment and other agents. Leveraging the independent nature of the agents, a conflict avoidance mechanism that models the crews’ behavior in real cases is also developed and integrated with them. In order to evaluate the proposed method, it was implemented in two case examples with distinct environments including a game engine and a commercial simulation tool. The analysis outcomes demonstrated the impact of the time-space conflicts on the crew productivity and provided crew size–project duration estimation as the quantified crashing modes. The method is expected to ameliorate the accuracy of the crashing analysis and help planners anticipate the emergent outcomes related to the different time-cost scenarios with associated risks.

Subject Keywords

Time-Space Conflicts, Agent-based Simulation, BIM, Time-Cost Trade-Off, Optimal Crew Size

URI

https://hdl.handle.net/11511/111490

Collections

Graduate School of Natural and Applied Sciences, Thesis