棚电式智能拖拉机远程操控界面注意力响应特性与优化设计
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山东省重点研发计划项目(2023CXGC010715)


Efficiency Response Characteristics and Optimization Design of Remote Control Interface for Shed Electric Intelligent Tractor
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    摘要:

    目前远程人机交互终端主要通过视频图像和数值图标进行堆叠式展示,但缺乏人因设计导致监控者在应对故障时信 息难以理解、心理负荷高,影响应急响应的可读性和准确性。本研究针对棚电式无人驾驶电动拖拉机远程终端堆叠式界面信息获取人因设计不足的问题,开发界面注意力采集系统,基于反应时间与识图准确率等注意力工效指标,开展对堆叠式界面无故障、突发单/两/三因素故障时的注意力工效试验,探析注意力工效对堆叠式应急界面的响应规律,分析界面人因 注意力分布场演变规律;开展人因工程学界面布局优化设计,对优化后的分布式界面与集中式界面进行试验验证,并综合评价界面注意力易读性与准确性的提升效果。研究结果表明,堆叠式界面、分布式界面、聚集式界面的单因素故障平均反应时间分别为1 096、1294、1 097 ms,两因素故障平均反应间分别为1123、1142、1293 ms,三因素故障最快发现预警反应时间分别为 820、1108、749 ms;注意力分布场分别呈现趋大模块性、趋高对比度性和趋中心性的分布规律,并分别呈向变化点、向显著点的演变规律;界面优化方案最终选取聚集式界面,其应急响应的平均反应时间较堆叠式界面降低3.4%、2 s内准确率平均提升11.66%、4 s 内准确率平均提升34.94%、监控者心理负荷降低11.99%。

    Abstract:

    At present, remote human-computer interaction terminals are mainly displayed in a stacked manner through video images and numerical icons. However, the lack of human factors design makes it difficult for monitors to understand information and has a high psychological load when dealing with faults, which affects the readability and accuracy of emergency response. Aiming to address the problem of insufficient human factors design in the remote terminal stacking interface information acquisition of unmanned electric tractors in facility greenhouses, an interface attention collection system was developed, and based on attention efficiency indicators such as reaction time and image recognition accuracy, attention efficiency experiments were conducted on the stacking interface when there were no faults and sudden single/two/three factor faults. The response law of attention efficiency to the stacking emergency interface was explored, and the evolution law of the distribution field of human factors attention on the interface was analyzed. Human factors engineering interface layout optimization design was carried out, the optimized distributed interface and centralized interface were verified through experiments, and the improvement effect of interface attention readability and accuracy was comprehensively evaluated. The research results showed that the average response time for single factor faults in stacked interfaces, distributed interfaces, and clustered interfaces were 1 096 ms, 1294 ms and 1 097 ms, respectively. The average response time for two factor faults was 1 123 ms, 1142 ms and 1293 ms, respectively. The fastest detection and warning response times for three factor faults were 820 ms, 1108 ms and 749 ms, respectively. The attention distribution fields exhibited distribution patterns of increasing modularity, increasing contrast, and centering, evolving towards change points and significant points, respectively. The interface optimization plan ultimately selected a clustered interface, which decreased the average response time of emergency response by 3.4% compared with that of a stacked interface, increased the average accuracy rate by 11.66% within 2 seconds and 34.94% within4 seconds, and reduced the psychological load on the monitor by 11.99%.

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张诚,胡楚文,罗振豪,宋正河,王英锋,宋来辉,杨晓.棚电式智能拖拉机远程操控界面注意力响应特性与优化设计[J].农业机械学报,2024,55(s1):392-404. ZHANG Cheng, HU Chuwen, LUO Zhenhao, SONG Zhenghe, WANG Yingfeng, SONG Laihui, YANG Xiao. Efficiency Response Characteristics and Optimization Design of Remote Control Interface for Shed Electric Intelligent Tractor[J]. Transactions of the Chinese Society for Agricultural Machinery,2024,55(s1):392-404.

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  • 收稿日期:2024-07-28
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  • 在线发布日期: 2024-12-10
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