Faridaddin Vahdatikhaki

Dynamic equipment workspace generation for improving earthwork safety using real-time location system

Display Omitted Earthwork equipment accounts for a large proportion of the fatalities on construction sites. According to the U.S. Bureau of Labor Statistics, in the period between 1992 and 2002, struck by vehicles and struck by objects (e.g., vehicle parts, vehicle loads, or falling vehicles) were identified as the causes of 30% and 24% of fatal equipment-related accidents on excavations sites, respectively. It is therefore of a paramount importance to improve the safety of construction sites by increasing the peripheral awareness of the operators of earthwork equipment. Several research works have investigated numerous collision avoidance systems that exploit real-time location systems and proximity measurements to mitigate the risk of accidents on excavation sites. However, these systems often detect collisions based on using the workspaces that only account for the geometry and the degrees of freedom of the equipment, and thus disregard the state-dependent characteristics of equipment. This results in reserving a large space for every piece of equipment, which reduces the applicability of these systems in congested sites. Therefore, this paper proposes a novel method for generating dynamic equipment workspaces based on the continuous monitoring of a spectrum of equipment-related information, i.e., the current pose/state of the equipment, and the speed characteristics of each movement. This method uses the required operation stoppage time to determine how much space needs to be reserved for each piece of equipment. A case study is conducted to validate the proposed method. It is shown that the proposed method has a strong potential in capturing the hazardous areas around the equipment and triggering warnings in view of the impending movements of various pieces of equipment. Also, the proposed method proved to have potential applications in actual projects in congested sites where space is limited.

Towards the smart construction site: improving productivity and safety of construction projects using multi-agent systems, real-time simulation and automated machine control

With the increasing complexity of construction projects grows the challenge of securing safety and achieving desirable productivity as the chief priorities of the construction industry. Addressing these issues requires robust mechanisms for on-site real-time data capturing, information processing and decision-making. The current research aims to further investigate the concept of the Smart Construction Site where workers, equipment, and materials are continuously tracked, and the collected information is processed in near real time to update the design model and the simulation of upcoming tasks, and to provide navigation guidance and safety warnings in case of potential collisions. The objective of our research is to improve the productivity and safety of heavy construction projects by integrating 3D design models (e.g. highway models) with the managerial and operational processes of heavy construction using advanced agent technology and multi-agent systems, real-time simulation, and automated machine control.

Real time safety risk analysis of construction projects using BIM and RTLS

The identification of potential accidents on construction sites has been a major concern in the construction industry and it needs a proactive safety plan to reduce the risk of accidents. There are no efficient methods for checking if safety measures are taken properly on construction sites. Consequently, workers on site are not given enough awareness about dangerous areas. In addition, construction sites are dynamic and on-site situations are changing in terms of permanent and temporary structures and facilities. This information can be represented using Building Information Modeling (BIM). This paper proposes the integration of BIM and safety risk analysis by considering the risk levels associated with the work spaces of different construction tasks. Work spaces are generated in a BIM model according to the Work Breakdown Structure (WBS) of the project, reference objects in the BIM, and the schedule and resources of the task. Each work space is assigned to one or more tasks or functions, e.g., work spaces for specific tasks, shared spaces (paths), storage spaces, or spaces prohibited to workers. The assignment of work spaces is based on the workers, equipment and materials involved in the task. All the work spaces are associated with a specific duration according to the schedule of the project. Then risk evaluation of the construction site is applied in order to evaluate safety risks based on their severity and the degree of exposure of workers. For example, work spaces for storing hazard materials and for heavy construction equipment have higher risks than other work spaces. The results of the risk evaluation can be visualized in a 4D BIM model.

Visibility and Proximity Based Risk Map of Earthwork Site Using Real-Time Simulation

Approximately 75% of struck-by fatalities in the construction industry are reported to have been caused by heavy equipment. Researchers have addressed the need for the enhanced safety of earthwork equipment using different approaches. However, none of these approaches enables the equipment to accurately predict the operation of other pieces of equipment for a long-enough time window to find a collision-free path using path replanning. Accordingly, the present paper proposes a novel method to generate the risk map of an earthwork site considering the visibility and proximity based hazards. The proposed method integrates the pose and state data of different pieces of equipment with the prediction about the potential paths of equipment, which comes from near-realtime simulation and script-based path planning, to quantify the risk value associated with different portions of the site. The generated risk map can further be used by individual equipment to ensure that their future path is safe or to perform path replanning if required. The proposed method is implemented and tested in a case study. In the light of the results of a case study, it is found that the proposed method is providing a reliable basis for the safety analysis of earthwork sites.

Location-aware real-time simulation framework for earthmoving projects using automated machine guidance

The cost-and-time-optimized planning of earthmoving projects has been significantly boosted as a result of deploying simulation techniques which enable project managers to effectively comprehend the behavior of projects. However, the realism and accuracy of the simulation models diminish as a result of the heavy reliance on the statistical data and of not taking into account the context-specific features of the project. Similarly, the more unique the characteristics of projects and novel the construction methods, the less the possibility of retrofitting a historic pattern to new projects. On the other hand, the identification of potential accidents on construction sites has been a major concern in the construction industry. To address these issues, this research proposes a framework based on the integration of new tracking technologies used in Automated Machine Guidance (AMG) with a real-time simulation technique. A prototype is developed to test and demonstrate the effectiveness of the proposed approach.

Real-Time Simulation of Earthmoving Projects Using Automated Machine Guidance

Simulation techniques have offered significant boosts toward a cost-and-time-optimized planning of construction projects by enabling project managers to effectively comprehend the behavior of projects. Using historic data from projects of like nature, simulation considers uncertainties involved in a project through accommodating the stochastic modeling parameters. However, the heavy reliance on the statistical data and not taking into account the context-specific features of the project cause the degradation in the realism and accuracy of the simulation models. Similarly, the extent to which a historic pattern could be retrofitted to new projects will decrease in line with the growing uniqueness of the projects and the novelty of construction methods. Furthermore, the existing real-time simulation frameworks are not capable of distinguishing the transient environmental changes, with minimal long-term impacts on the productivity, from the influential changes that will greatly impact an operation. In addition, existing simulation tools are devoid of location awareness, resulting in the inability to consider safety threats in their representation of the project. To address these issues, this research proposes a framework based on the integration of new tracking technologies used in Automated Machine Guidance (AMG) with simulation-driven 4D modeling methods. The proposed framework automates the adjustment of the simulation model based on the updated data from the site, and thus transforms simulation from a predictive tool used at the planning phase to a proactive monitoring platform usable throughout the planning and construction phases. A prototype is developed to test and demonstrate the effectiveness of the proposed approach.

Decision Support for Test Trench Location Selection with 3D Semantic Subsurface Utility Models

Subsurface utility construction work often involves repositioning of, and working between, existing buried networks. While the amount of utilities in modern cities grows, excavation work becomes more prone to incidents. To prevent such incidents, excavation workers request existing 2D utility maps, use detection equipment and dig test trenches to validate their accuracy and completeness. Although test trenches are of significant importance to reveal information about subsurface conditions, the process of determining their location, number and size is not explicated by experts to date. This study therefore aimed to explicate the reasoning and logic behind the selection of utility test trenches, and to formalize this in a semantically-rich utility model. To this end, we conducted interviews with experienced excavator operators. We then derived heuristics and rules that the experts used to determine trench locations. Such rules related to, for example, the layout of the excavation site, and the type of utilities, and accuracy of available data. Based on these rules, we integrated various incomplete sources of data, and generated a 3D utility model that could generate several alternative construction situations. We used queries to identify the most suitable location for a test trench. The resulting answers to queries helped optimize the test trench selection process. Our prototype demonstrates that the identified rules (1) facilitate the generation of semantically rich 3D utility models, and (2) support test trench decision making.

Towards Developing an Ontology for Earthwork Operations

In a typical construction project, a significant amount of information is communicated to various stakeholders at different phases of the project lifecycle. The communication of this information tends to be informal and ad-hoc in the majority of the cases, which makes it more susceptible to loss of information or misinterpretation. Earthwork operations, which are one of the main operations of construction projects, also struggle with the challenge of effective information communication. There is an apparent shortcoming regarding the unified structure for data and information exchange in this domain. The existing models and ontologies do not address the explicit semantic representation of the earthwork operations. Accordingly, there is a need for a knowledge model to formalize the communication of information in an efficient manner. An ontological model can be used to organize the domain knowledge so that it can be utilized and reused by the stakeholders, e.g., project managers, designers, etc. This paper purposes a framework to develop an ontology for earthwork operations to support and enhance data exchange and communication among different stakeholders in the project. The main objectives of this paper are (1) to formalize the knowledge in the earthwork domain, and (2) to build an ontology that captures this formalization. The ultimate result of this ontology, which is demonstrated by means of a case study, is to facilitate the development of data standards that can be shared in actual projects to accelerate project execution.

Dynamic Equipment Workspace Generation for Improving Earthwork Safety Using Equipment Pose and State Data

In the period between 1992 and 2002, struck by vehicles and struck by objects (e.g., vehicle parts, vehicle loads, or falling vehicles) were identified as the causes of 30% and 24% of deaths on excavations sites, respectively. It is therefore of a paramount importance to improve the safety of construction sites by increasing the peripheral awareness of the operators of earthwork equipment. The existing collision avoidance systems often detect collisions based on the workspaces that only account for the geometry and the degrees of freedom of the equipment, and thus disregard the job-site-andstate-dependent characteristics of equipment. This results in reserving a large space for every piece of equipment. Therefore, this paper proposes a novel method for generating dynamic equipment workspaces based on the continuous monitoring of a spectrum of equipment-related information, i.e., the current pose/state of the equipment, and the speed characteristics of each movement. This method uses the required operation stoppage time to determine how much space needs to be reserved for each piece of equipment. A case study is conducted to validate the proposed method. It is shown that the proposed method has a strong potential in capturing the hazardous areas around the equipment and triggering warnings in view of the impending movements of various pieces of equipment.