Micro-scale spatial modification and pedestrian behavior

Abstract

This paper proposes a flexible framework for hypothesis testing of behavioral changes in pedestrians in field environments and provides a case study demonstrating its application. The framework employs computer-vision-based 3D tracking using existing CCTV networks to collect uncontrolled, ecological data of pedestrian movement and extracts the nature and duration of pedestrian behaviors without prior assumptions. To evaluate the framework, we conducted a case study in a specialty retailer where, after collecting control data, pedestrian flow was intentionally constricted by introducing in-aisle obstacles. We observed a marked rise in traversal and navigation of the aisle accompanied by reductions in browsing and deliberation. We conclude that this framework offers utility in optimizing retail environments and can be generalized to model the effects of environmental changes on behavior in spaces where loitering, dwell time, or free flow of traffic are relevant design considerations.