Chapter
Mar 18, 2024

Development of a Rule-Based Safety Checking System for Autonomous Heavy Construction Equipment

Publication: Construction Research Congress 2024

ABSTRACT

Highway and road construction and maintenance involve operations of heavy construction equipment consistently exposing workers to injuries and fatalities. Frequent collisions between heavy equipment and workers on foot cause many deaths and disabilities. A large portion of these work zone fatalities, such as being struck by equipment and caught in/between equipment, can be effectively prevented by automatically detecting objects around the equipment, determining their poses and movements, and eventually alerting operators and workers about unsafe situations. This study attempts to embed a situational awareness to heavy construction equipment by integrating sensing technologies into heavy construction equipment. This study developed a Robots Operating System (ROS)-based software program to determine the placement of multiple sensors ensuring 360-degree visibility around the equipment and process the sensor data into an accurate 3D representation of the work zone environment to detect predefined unsafe situations. The prototype safety monitoring system evaluated in a simulated road construction environment successfully detected the presences and locations of human workers around the equipment.

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REFERENCES

Geiger, A., Lenz, P., and Urtasun, R. (2012). Are we ready for autonomous driving? the KITTI vision benchmark suite. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. https://doi.org/10.1109/CVPR.2012.6248074.
Gómez-de-Gabriel, J. M., Fernández-Madrigal, J. A., López-Arquillos, A., and Rubio-Romero, J. C. (2019). Monitoring harness use in construction with BLE beacons. Measurement: Journal of the International Measurement Confederation, 131. https://doi.org/10.1016/j.measurement.2018.07.093.
Koenig, N., and Howard, A. (2004). Design and use paradigms for Gazebo, an open-source multi-robot simulator. 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 3. https://doi.org/10.1109/iros.2004.1389727.
Li, J., Carr, J., and Jobes, C. (2012). A shell-based magnetic field model for magnetic proximity detection systems. Safety Science, 50(3). https://doi.org/10.1016/j.ssci.2011.10.007.
Parekh, D., Poddar, N., Rajpurkar, A., Chahal, M., Kumar, N., Joshi, G. P., and Cho, W. (2022). A Review on Autonomous Vehicles: Progress, Methods and Challenges. Electronics, 11(14), 2162. https://doi.org/10.3390/electronics11142162.
Park, J., Marks, E., Cho, Y. K., and Suryanto, W. (2016). Performance Test of Wireless Technologies for Personnel and Equipment Proximity Sensing in Work Zones. Journal of Construction Engineering and Management, 142(1). https://doi.org/10.1061/(asce)co.1943-7862.0001031.
Park, J. W., Chen, J., and Cho, Y. K. (2017). Self-corrective knowledge-based hybrid tracking system using BIM and multimodal sensors. Advanced Engineering Informatics, 32. https://doi.org/10.1016/j.aei.2017.02.001.
Qi, C. R., Liu, W., Wu, C., Su, H., and Guibas, L. J. (2018). Frustum PointNets for 3D Object Detection from RGB-D Data. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. https://doi.org/10.1109/CVPR.2018.00102.
Redmon, J., Divvala, S., Girshick, R., and Farhadi, A. (2016). You only look once: Unified, real-time object detection. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2016-December. https://doi.org/10.1109/CVPR.2016.91.
SAE International. (2018). Taxonomy and Definitions for Terms Related to Driving Automation Systems for On-Road Motor Vehicles J3016. In SAE International (Vol. J3016, Issue J3016).
Van Brummelen, J., O’Brien, M., Gruyer, D., and Najjaran, H. (2018). Autonomous vehicle perception: The technology of today and tomorrow. In Transportation Research Part C: Emerging Technologies (Vol. 89). https://doi.org/10.1016/j.trc.2018.02.012.
Wang, W. (2021). Construction Technology and Safety Monitoring Measures of Road and Bridge Engineering. Journal of Architectural Research and Development, 5(5). https://doi.org/10.26689/jard.v5i5.2542.
Yu, H., Liu, F., and Wang, Y. (2022). Construction and Evaluation of Construction Safety Management System Based on BIM and Internet of Things. In Security and Communication Networks (Vol. 2022). https://doi.org/10.1155/2022/1541241.
Zacharaki, A., Kostavelis, I., Gasteratos, A., and Dokas, I. (2020). Safety bounds in human robot interaction: A survey. In Safety Science (Vol. 127). https://doi.org/10.1016/j.ssci.2020.104667.
Zhu, C., Zhu, J., Bu, T., and Gao, X. (2022). Monitoring and Identification of Road Construction Safety Factors via UAV. Sensors, 22(22). https://doi.org/10.3390/s22228797.

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Go to Construction Research Congress 2024
Construction Research Congress 2024
Pages: 962 - 971

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Published online: Mar 18, 2024

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Amirpooya Shirazi [email protected]
1M.S. Student, Durham School of Architectural Engineering & Construction, Univ. of Nebraska–Lincoln, Omaha, NE. Email: [email protected]
Kyungki Kim [email protected]
2Assistant Professor, Durham School of Architectural Engineering & Construction, Univ. of Nebraska–Lincoln, Omaha, NE. Email: [email protected]

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