Modeling novice law enforcement officers’ interaction with in-vehicle technology
Modeling novice law enforcement officers’ interaction with in-vehicle technology
复制标题
对新手执法人员与车载技术的交互进行建模
DOI：
10.1016/j.apergo.2023.104154
复制
发表时间：
2024
影响因子：
3.2
通讯作者：
Zahabi, Maryam
中科院分区：
文献类型：
--
作者：
Park, Junho;Wozniak, David;Zahabi, Maryam
认知性能模型已被用于多个人因领域，如驾驶和人机交互。然而，大多数模型仅限于专家的表现，尽管先前的研究表明新手的认知，感知和运动行为与专家不同，但仍对新手进行了粗略的调整。本研究的目的是开发一个新的执法人员（N-CPM）的认知性能模型，以模拟他们的性能和记忆负荷，同时与车载技术进行交互。该模型进行了验证的基础上，与10个新手执法人员（nLEO）的乘车研究。结果表明，在大多数情况下，N-CPM和观察数据之间没有显着差异，而基准模型的结果与N-CPM的结果不同。该模型可用于提高未来nLEO的巡逻使命性能，通过重新设计的车载技术和训练方法，以减少他们的工作量和驾驶分心。
Cognitive performance models have been used in several human factors domains such as driving and human-computer interaction. However, most models are limited to expert performance with rough adjustments to consider novices despite prior studies suggesting novices' cognitive, perceptual, and motor behaviors are different from experts. The objective of this study was to develop a cognitive performance model for novice law enforcement officers (N-CPM) to model their performance and memory load while interacting with in-vehicle technology. The model was validated based on a ride-along study with 10 novice law enforcement officers (nLEOs). The findings suggested that there were no significant differences between the N-CPM and observation data in most cases, while the results of the benchmark model were different from that of N-CPM. The model can be applied to improve future nLEO's patrol mission performance through redesigning in-vehicle technologies and training methods to reduce their workload and driving distraction.