# Dynamics of Pedestrian Crossing Decisions Based on Vehicle Trajectories in Large-Scale Simulated and Real-World Data

## TL;DR

This paper investigates how the dynamic trajectories of vehicles influence pedestrian crossing decisions, emphasizing the role of non-verbal cues like trajectory changes in both simulated and real-world large-scale datasets.

## Contribution

It provides new evidence that vehicle trajectory dynamics serve as important non-verbal signals affecting pedestrian crossing choices, expanding understanding beyond traditional TTA-based models.

## Key findings

- Trajectory dynamics significantly influence pedestrian crossing decisions.
- Changes in TTA are powerful signals in non-verbal communication.
- Large-scale real-world data confirms the importance of trajectory cues.

## Abstract

Humans, as both pedestrians and drivers, generally skillfully navigate traffic intersections. Despite the uncertainty, danger, and the non-verbal nature of communication commonly found in these interactions, there are surprisingly few collisions considering the total number of interactions. As the role of automation technology in vehicles grows, it becomes increasingly critical to understand the relationship between pedestrian and driver behavior: how pedestrians perceive the actions of a vehicle/driver and how pedestrians make crossing decisions. The relationship between time-to-arrival (TTA) and pedestrian gap acceptance (i.e., whether a pedestrian chooses to cross under a given window of time to cross) has been extensively investigated. However, the dynamic nature of vehicle trajectories in the context of non-verbal communication has not been systematically explored. Our work provides evidence that trajectory dynamics, such as changes in TTA, can be powerful signals in the non-verbal communication between drivers and pedestrians. Moreover, we investigate these effects in both simulated and real-world datasets, both larger than have previously been considered in literature to the best of our knowledge.