Developing an Agent-Based Simulation Model for Predicting Technology Acceptance at Border Crossing Points

Sarang Shaikh, Sule YAYILGAN YILDIRIM
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Abstract

In this paper, we are focusing on the use of agent-based approach to generate simulations of various scenarios for border crossing points and making technology acceptance predictions. This paper is related to the Horizon 2020 project METICOS11https://meticos-project.eu/, for which we are extracting user (traveler and border control staff) perceptions from sources such as online social networks e.g., Twitter, Web, Interviews, Questionnaires etc. However, for the scope of this paper we have only included the synthetic data for the experiments to validate the proposed simulation model. The existing studies made a strong justification for choosing this approach to model the defined problem. To the best of our knowledge, this paper is a first research study focusing on defining how agent-based modeling and simulation can be used to model border crossing scenarios and predicting the acceptance of the border control technologies by explaining travelers' profile based on synthetic data, perceptions based on manual rules. This is important for stakeholders who take decisions related to what technologies to place at the border crossing points and what features such technologies should have to improve throughputs and traveler and border staff satisfaction.
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基于agent的边境口岸技术接受度预测仿真模型研究
在本文中,我们专注于使用基于代理的方法来生成边境过境点各种场景的模拟,并进行技术接受度预测。本文与地平线2020项目METICOS11https://meticos-project有关。eu/,为此,我们从在线社交网络(如Twitter、Web、访谈、问卷等)中提取用户(旅行者和边境管制人员)的看法。然而,在本文的范围内,我们只包括了实验的综合数据,以验证所提出的仿真模型。现有的研究为选择这种方法对已定义的问题建模提供了强有力的理由。据我们所知,本文是第一个研究如何使用基于主体的建模和仿真来建模过境场景,并通过基于合成数据和基于人工规则的感知来解释旅行者的个人资料,从而预测边境控制技术的接受程度的研究。这对于决定在过境点采用何种技术以及这些技术应该具有哪些特性以提高吞吐量以及旅客和边境工作人员满意度的利益相关者来说非常重要。
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