A binary acceleration signal reduces overestimation in pedestrians’ visual time-to-collision estimation for accelerating vehicles

Wessels, Marlene; Oberfeld, Daniel

doi:10.1016/j.heliyon.2024.e27483

Heliyon

2024

DOI: 10.1016/j.heliyon.2024.e27483

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A binary acceleration signal reduces overestimation in pedestrians’ visual time-to-collision estimation for accelerating vehicles

Marlene Wessels,

Daniel Oberfeld

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2024

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A Dynamic Algorithm for Measuring Pedestrian Congestion and Safety in Urban Alleyways

Lee,

Kang

2024

IJGI

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This study presents an algorithm for measuring Pedestrian Congestion and Safety on alleyways, wherein pedestrians and vehicles share limited space, making traditional pedestrian density metrics inadequate. The primary objective is to provide a more accurate assessment of congestion and safety in these shared spaces by incorporating both pedestrian and vehicle interactions, unlike traditional methods that focus solely on pedestrians, regardless of road type. Pedestrian Congestion was calculated using Time to Collision (TTC)-based safety occupation areas, while Pedestrian Safety was assessed by accounting for both physical and psychological safety through proxemics, which measures personal space violations. The algorithm dynamically adapts to changing vehicle and pedestrian movements, providing a more accurate assessment of congestion compared to existing methods. Statistical validation through t-tests and K-S (Kolmogorov–Smirnov) tests confirmed significant differences between the proposed method and traditional pedestrian density metrics, while Bland–Altman analysis demonstrated agreement between the two methods. The experimental results reveal that Pedestrian Congestion and Safety varied with time and location, capturing the spatio-temporal characteristics of alleyways. Visual comparisons of Pedestrian Congestion, Safety, and Density further validated that the proposed algorithm provides a more accurate reflection of real-world conditions compared to traditional pedestrian density metrics. These findings highlight the algorithm’s ability to measure real-time changes in congestion and safety, incorporate psychological discomfort into safety calculations, and offer a comprehensive analysis by considering both pedestrian and vehicle interactions.

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A Dynamic Algorithm for Measuring Pedestrian Congestion and Safety in Urban Alleyways

Lee,

Kang

2024

IJGI

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A binary acceleration signal reduces overestimation in pedestrians’ visual time-to-collision estimation for accelerating vehicles

Cited by 1 publication

References 60 publications

A Dynamic Algorithm for Measuring Pedestrian Congestion and Safety in Urban Alleyways

A Dynamic Algorithm for Measuring Pedestrian Congestion and Safety in Urban Alleyways

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