一项测量影响出行选择的认知偏误的调查
A survey to measure cognitive biases influencing mobility choices
AI总结：
本文基于650份出行调查数据，分析光环偏误、选择支持偏误和心理抗拒三种认知偏误对出行方式选择的影响，为构建出行决策模拟器和可持续城市规划严肃游戏提供模型与数据基础。
摘要：
本文描述了一项关于4种出行方式（汽车、公交车、自行车、步行）的感知以及用户对6种方式选择因素偏好的调查。该调查在2023年收集了650份回答，并已作为开放数据发布。在本研究中，我们分析这些结果，以揭示3种认知偏误对出行决策的影响：光环偏误、选择支持偏误和心理抗拒。这些认知偏误被提出作为所观察行为的合理解释，即尽管城市政策旨在鼓励软性出行，但人群仍倾向于坚持使用私家车。该模型可作为虚拟城镇中出行决策模拟器的基础，所收集的数据可用于为该人群赋予现实属性。目前正在进行一项基于模拟的严肃游戏设计工作，玩家将扮演城市管理者，面对规划选择以使城市更加可持续。
英文摘要：
In this paper, we describe a survey about the perceptions of 4 mobility modes (car, bus, bicycle, walking) and the preferences of users for 6 modal choice factors. This survey has gathered 650 answers in 2023, that are published as open data. In this study, we analyse these results to highlight the influence of 3 cognitive biases on mobility decisions: halo bias, choice-supportive bias, and reactance. These cognitive biases are proposed as plausible explanations of the observed behaviour, where the population tends to stick to individual cars despite urban policies aiming at favouring soft mobility. This model can serve as the basis for a simulator of mobility decisions in a virtual town, and the gathered data can be used to initialise this population with realistic attributes. Work is ongoing to design a simulation-based serious game where the player takes the role of an urban manager faced with planning choices to make their city more sustainable.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
