Wang, Z; Yan, X; Liu, Q; Ma, X and Li, H (2026) Vision-based collision prevention on construction sites: Integrating trajectory prediction and uncertainty modeling. Journal of Construction Engineering and Management, 152(1): 04025214, ISSN 0733-9364
Abstract
Collisions between workers and vehicles are a leading cause of fatalities on construction sites around the world. While automation technology has been extensively applied to various aspects of construction safety management, including collision prevention, significant inaccuracies in estimating safe distances between workers and vehicles, coupled with limited hazard prediction capabilities, continue to hinder efforts to effectively prevent collision accidents on construction sites. To address these challenges, this study proposes a novel collision prevention method that integrates computer vision and trajectory prediction technologies. First, the You Only Look Once version 11 (YOLOv11) model and simple online and realtime tracking (SORT) algorithm were employed to accurately detect and track workers and vehicles, effectively extracting their movement trajectories in dynamic construction scenarios. Second, a transformer-based trajectory prediction algorithm was developed, enabling high-precision motion forecasting and providing critical data for risk region definition and collision warning. Finally, a dynamic risk region division method was designed, incorporating motion states and positional uncertainty to identify potential collision risks in real time. Experimental results demonstrated that the proposed system achieved over 90% accuracy in detecting workers and vehicles and successfully extracted their trajectories. The transformer-based prediction algorithm showed excellent short-term accuracy, providing reliable trajectory forecasts. Furthermore, the risk region definition method effectively identified potential collision areas, including those occurring during vehicle turning maneuvers. In summary, the proposed method performs well in complex scenarios, accurately predicting risk regions, including collision risks during vehicle turning maneuvers. This study provides a reliable and efficient solution for proactive collision prevention, offering robust technical support for improving safety management and reducing accidents in construction environments.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | collision prevention; computer vision; trajectory prediction; transformer |
| Index terms: | real time, fatalities, automation, prevention, forecasting, safety management, construction safety, estimating, uncertainty modelling, computer vision, movement, construction site, accuracy |
| Subjects: | health behaviours and lifestyles, financial risk, automation and robotics, computer vision, environmental hazards, prediction and forecasting, financial and cost management, work location, professional development, health risk and incident analysis, environmental health, project controls, occupational health and safety management |
| Topics: | Sustainability, Health and Safety, Cost Management, Research Practice, Information Management, Time Control, Site Management, Digital Applications |
| Descriptive scope: | 3 PCA |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here