用户在多目标路线上的偏好:梯度可视化的作用和个性测量
Keisuke Otaki1, Takayoshi Yoshimura1
1Toyota Central R&D Labs., Inc., Bunkyo-ku, Tokyo, Japan.
PloS one
|August 6, 2025
概括
导航系统需要考虑的不仅仅是距离. 这项研究表明,呈现路线梯度信息会影响行人选择,像感觉寻找这样的个性特征在路线偏好中起着关键作用.
科学领域:
- 城市规划和人与计算机的互动.
- 心理学和行为科学.
背景情况:
- 传统的行人导航系统专注于最短或最快的路线.
- 现代城市导航需要多个目标考虑,如梯度,熟悉度和个人偏好.
研究的目的:
- 调查梯度信息呈现 (数值与图形) 对行人路线选择的影响.
- 探索个人心理特征 (五大特征,感觉寻求) 对这些决策的影响.
主要方法:
- 一项在线调查,91名参与者被随机分配到控制,数值梯度或图形梯度组.
- 参与者从优化斜率和距离的对中选择了他们喜欢的路线.
- 分析与梯度信息和心理资料相关的路线选择.
主要成果:
- 数字梯度呈现适度减少了最短路线的选择,特别是在更长的路线上.
- 图形梯度表示在决策中并没有显著优于数值格式.
- 更高的感觉寻找得分与更长,更温和的路线的偏好相关 (p < 0.01).
结论:
- 梯度信息影响行人路线选择,数字格式显示的效果很小.
- 个人心理特征,特别是感觉寻找,显著影响路线偏好.
- 个性化导航系统可以从整合用户心理概况中获益,以改进路线建议.
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