Exploring Pedestrian's Visual Attention and Walkability Preference in Nighttime Commercial Street Using Eye-Tracking

This study explores the relationship between pedestrian's visual attention and walkability preference in nighttime commercial street, using East Nanjing Road in Shanghai as a case study. Eye-tracking data were collected from 46 participants viewing 34 images with walkability preferences assessed through self-reports. Environmental elements were identified and categorized using semantic recognition and the images were divided into high-walkability preference (HWP) and low-walkability preference (LWP) groups. Differences in fixation duration, fixation count, and information density (calculated as the ratio of subjective fixation proportion to objective area proportion) were analyzed. Results show that buildings attracted the longest fixation duration and the most fixation counts, followed by people among all images. Across both groups, lighting elements exhibited high information density, buildings had medium density, while green plants and the sky showed relatively low density. Notable differences emerged between groups, with participants in the LWP group paying more visual attention to advertisements. This study provides insights into pedestrians' visual attention in nighttime commercial streets, informing the design of urban walking environments after dark.

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Publication Details

Published
2024-11-12
DOI
https://doi.org/10.1109/ls2463127.2024.10880898
Primary Topic
Urban Transport and Accessibility
Type
article
Field-Weighted Citation Impact
0.00

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article

Exploring Pedestrian's Visual Attention and Walkability Preference in Nighttime Commercial Street Using Eye-Tracking

Xianxian Zeng, Shenfei Chen, Yi Lin
Urban Transport and Accessibility
article

Exploring Pedestrian's Visual Attention and Walkability Preference in Nighttime Commercial Street Using Eye-Tracking

Xianxian Zeng, Shenfei Chen, Yi Lin
article en

Abstract

This study explores the relationship between pedestrian's visual attention and walkability preference in nighttime commercial street, using East Nanjing Road in Shanghai as a case study. Eye-tracking data were collected from 46 participants viewing 34 images with walkability preferences assessed through self-reports. Environmental elements were identified and categorized using semantic recognition and the images were divided into high-walkability preference (HWP) and low-walkability preference (LWP) groups. Differences in fixation duration, fixation count, and information density (calculated as the ratio of subjective fixation proportion to objective area proportion) were analyzed. Results show that buildings attracted the longest fixation duration and the most fixation counts, followed by people among all images. Across both groups, lighting elements exhibited high information density, buildings had medium density, while green plants and the sky showed relatively low density. Notable differences emerged between groups, with participants in the LWP group paying more visual attention to advertisements. This study provides insights into pedestrians' visual attention in nighttime commercial streets, informing the design of urban walking environments after dark.

Tongji University (CN), Fudan University (CN), Shanghai Tongji Urban Planning and Design Institute (CN)
National Natural Science Foundation of China
Sustainable cities and communities
Openalex Percentile: Top 75%
Urban Transport and Accessibility
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