Autonomous driving paper index

Trust as a mediator between physical climate conditions and human–robot collaboration efficiency in construction

2026-07-18 · Automation in Construction

autonomous driving

One-line summary

Human–robot collaborative performance is influenced by physical workplace conditions, which can affect performance indirectly through workers' physiological comfort, cognitive load, and situational awareness.

Engineering notes

Trust also significantly mediates the effect of environment on performance.

Chinese explanation / 中文解读

中文解读待补充:本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。

Original abstract

Human–robot collaborative performance is influenced by physical workplace conditions, which can affect performance indirectly through workers' physiological comfort, cognitive load, and situational awareness. Under summer high-temperature conditions, construction sites impose increased environmental constraints on collaboration. This paper investigates how adverse summer working environments influence human–robot collaboration efficiency, and whether workers' trust in robots mediates this relationship. A pilot experiment was conducted using a representative rebar-tying task to compare human–robot collaboration in two construction environments: a relatively comfortable, factory-like environment enabled by an aerial building machine (ABM) and a conventional non-ABM environment characterized by more adverse working conditions. Results show that the ABM environment improves collaborative efficiency by approximately 19.8% and enhances trust. Trust also significantly mediates the effect of environment on performance. These findings offer insights into human–robot collaboration and guide intelligent construction under high-temperature conditions.

5.0Engineering value
7.0Research novelty
5.0Business relevance

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