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AlChaer, E and Issa, C A (2020) Engineering Productivity Measurement: A Novel Approach. Journal of Construction Engineering and Management, 146(08).
Cai, S, Ma, Z, Skibniewski, M J, Bao, S and Wang, H (2020) Construction Automation and Robotics for High-Rise Buildings: Development Priorities and Key Challenges. Journal of Construction Engineering and Management, 146(08).
Chen, Y, Chen, S, Hu, C, Jin, L and Zheng, X (2020) Novel Probabilistic Cost Estimation Model Integrating Risk Allocation and Claim in Hydropower Project. Journal of Construction Engineering and Management, 146(08).
Han, Y, Yin, Z, Zhang, J, Jin, R and Yang, T (2020) Eye-Tracking Experimental Study Investigating the Influence Factors of Construction Safety Hazard Recognition. Journal of Construction Engineering and Management, 146(08).
- Type: Journal Article
- Keywords: Eye-tracking; Construction safety; Safety education; Hazard detection; Cognitive load;
- ISBN/ISSN: 0733-9364
- URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0001884
- Abstract:
Construction site accidents can be reduced if hazards leading to accidents are correctly and promptly detected by employees. Proactive safety measures such as safety perception and safety detection capability of employees play an important role in improving the safety performance. This study was initiated by three research questions related to (1) the measurement indicators of employees’ cognitive load in recognizing safety hazards; (2) site condition factors (e.g., brightness) that can affect subjects’ cognitive load; and (3) the quantification of the effects of these site factors on cognitive load. An eye-tracking experimental approach was adopted by recruiting a total of 55 students from construction management or other civil engineering disciplines to visually search hazards in 20 given site scenes. These site scenes were defined by a combination of three different categories, namely distinctiveness of hazards, site brightness, and tidiness. Quantitative measurements of experimental participants’ visual search patterns were obtained from data captured by the eye-tracking apparatus. Based on metrics related to experimental participants’ fixation, visual search track, and attention map, these measurements were computed to evaluate participants’ cognitive load in detecting hazards. Descriptive statistical comparisons analyzed these metrics under predefined categories of site conditions, i.e., distinctness versus obscurity/blurriness, brightness versus darkness, and tidiness versus messiness. The findings revealed that distinct site conditions reduced participants’ time in saccades to search hazards but did not improve the accuracy rate of first fixation; messy sites with disorganized items increased participants’ cognitive load in detecting hazards in terms of all five measurement items (i.e., accuracy rate of first fixation, fixation count, intersection coefficient, fixation duration, and fixation count in the attention center); the effect of increased brightness on-site needs further studies to determine the optimal balance of brightness level and allocation. Recommendations based on the findings were provided to enhance safety education in terms of site hazard distinctiveness, brightness, and housekeeping best practice. This study extended a few prior studies of adopting eye-tracking technology for safety monitoring by evaluating the impacts of site conditions on participants’ cognitive load, which was linked to their hazard detection performance. The study provided insights for evaluating construction employees’ hazard detection capabilities to enhance safety education. Future work is proposed to evaluate employees’ safety hazard detection pattern under dynamic construction scenarios.
Ibrahim, M W, Hanna, A S, Russell, J S, Abotaleb, I S and El-adaway, I H (2020) Quantitative Analysis of the Impacts of Out-of-Sequence Work on Project Performance. Journal of Construction Engineering and Management, 146(08).
Jiang, Y and Bai, Y (2020) Estimation of Construction Site Elevations Using Drone-Based Orthoimagery and Deep Learning. Journal of Construction Engineering and Management, 146(08).
Kim, J J, Miller, J A and Kim, S (2020) Cost Impacts of Change Orders due to Unforeseen Existing Conditions in Building Renovation Projects. Journal of Construction Engineering and Management, 146(08).
Li, H, Lv, L, Zuo, J, Su, L, Wang, L and Yuan, C (2020) Dynamic Reputation Incentive Mechanism for Urban Water Environment Treatment PPP Projects. Journal of Construction Engineering and Management, 146(08).
Li, J, Wang, H, Xie, Y and Zeng, W (2020) Human Error Identification and Analysis for Shield Machine Operation Using an Adapted TRACEr Method. Journal of Construction Engineering and Management, 146(08).
Ryu, J, Alwasel, A, Haas, C T and Abdel-Rahman, E (2020) Analysis of Relationships between Body Load and Training, Work Methods, and Work Rate: Overcoming the Novice Mason’s Risk Hump. Journal of Construction Engineering and Management, 146(08).
Sonmez, R, Aminbakhsh, S and Atan, T (2020) Activity Uncrashing Heuristic with Noncritical Activity Rescheduling Method for the Discrete Time-Cost Trade-Off Problem. Journal of Construction Engineering and Management, 146(08).
Tan, T, Lu, W, Tan, G, Xue, F, Chen, K, Xu, J, Wang, J and Gao, S (2020) Construction-Oriented Design for Manufacture and Assembly Guidelines. Journal of Construction Engineering and Management, 146(08).
Yin, X, Chen, Y, Bouferguene, A, Zaman, H, Al-Hussein, M and Russell, R (2020) Data-Driven Framework for Modeling Productivity of Closed-Circuit Television Recording Process for Sewer Pipes. Journal of Construction Engineering and Management, 146(08).
Zhan, W and Pan, W (2020) Formulating Systemic Construction Productivity Enhancement Strategies. Journal of Construction Engineering and Management, 146(08).
Zhang, R P, Lingard, H and Oswald, D (2020) Impact of Supervisory Safety Communication on Safety Climate and Behavior in Construction Workgroups. Journal of Construction Engineering and Management, 146(08).
Zheng, J, Wen, Q and Qiang, M (2020) Understanding Demand for Project Manager Competences in the Construction Industry: Data Mining Approach. Journal of Construction Engineering and Management, 146(08).
Zhu, L, Cheung, S O, Gao, X, Li, Q and Liu, G (2020) Success DNA of a Record-Breaking Megaproject. Journal of Construction Engineering and Management, 146(08).