Pedestrian crossing behavior and visual attention under flashing green countdown signals

Abstract

The interaction between signal-controlled intersection and pedestrian primarily relies on pedestrian traffic signals. With increasing pedestrian-related intersection accidents, it is imperative to investigate pedestrian behavior particularly under flashing green countdown signals. This experiment was conducted at a real-world signal-controlled intersection in Changsha City, China, where 30 university students (aged 20–28, with a balanced gender distribution) wore eye-tracking glasses and motion sensor while crossing the street. This study investigated the mechanism through which pedestrian countdown signals (PCS) affect pedestrian crossing behavior and visual attention under mobile phone distraction and time constraint, while exploring the differences in pedestrian behavior before and after the flashing green countdown signals. The results reveal that flashing green countdown signals prompted pedestrians to redirect their visual attention toward the PCS, enhancing the efficiency of visual information processing while significantly facilitating faster crossings. However, mobile phone distraction weakened these positive effects of PCS, reducing the likelihood of shifting visual attention toward the PCS and decreasing the relative speed change rate by 55%, while also increasing the rate of green phase crossing incompletion. Besides, this study indicates that pedestrians had a significantly reduced level of attention to the PCS under crossing time constraints, whereas attention to the zebra crossing area increased. Flashing green countdown signals had a stronger impact on pedestrians’ speed characteristics under limited crossing time, with crossing speed variation being 2.71 times more pronounced after PCS green light flashing, while the probability of visual attention shifts to the PCS decreased. These findings are significant for understanding the mechanisms by which the flashing green signal affects pedestrians and may provide a scientific basis for future intersection management policies and intelligent transportation infrastructure.