%0 Journal Article
%T 行车历史数据提取模型设计与研究<br>Design and Research of Driving History Data Extraction Model
%A 张航铭
%J Artificial Intelligence and Robotics Research
%P 9-16
%@ 2326-3423
%D 2023
%I Hans Publishing
%R 10.12677/AIRR.2023.121002
%X 车内人机交互(HMI)系统已经发展成为汽车必备的一个“零件”。作为计算机科学、行为科学以及其他几个研究领域的交汇处，车内HMI在实际应用领域中具有巨大的潜在价值。然而，现有的HMI交互内容大部分为指令或者公共数据等不涉及到驾驶员和驾驶数据，造成了HMI在个性化服务上的数据缺失问题。因此，本文构建了行车历史数据提取模型，通过真实环境下的行车视频数据，提取出与行车过程中有联系的目标集合以及目标对应的时间集合和位置集合，最后将提取出的数据持久化到本地。除此之外，本文设计的性能测试实验证明了此模型技术方案的可行性和准确性。<br />
In-vehicle Human-Machine Interaction (HMI) system has developed into an essential “part” of the car. As the intersection of computer science, behavioral science, and several other research fields, in-vehicle HMI has great potential value in the field of practical application. However, most of the existing HMI interaction content is instructions or public data, which does not involve the driver and driving data, resulting in the lack of data in the personalized service of HMI. Therefore, this paper constructs a driving history data extraction model. Through the driving video data in the real environment, the target set related to the driving process and the time set and location set corresponding to the target are extracted, and finally the extracted data is persisted to local. In addition, the performance test experiment designed in this paper proves the feasibility and accuracy of the technical solution of this model.
%K 车内人机交互，行车历史数据<br>In-Vehicle Human-Computer Interaction
%K Driving History Data
%U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=61828