Navigating Shared Space: A Preliminary Field Study Analyzing Pedestrian Path Modifications in Response to Autonomous Sidewalk Robots
Authors: Marohn Robert 
Published: February 2025

As autonomous robots become more common in urban environments, understanding interactions with pedestrians is crucial for ensuring smooth human-robot coexistence. Serve Robotics, a leader in sustainable urban logistics, operates autonomous sidewalk robots in West Hollywood, California, USA delivering food and packages. These robots, guided by sensors and AI, navigate pedestrian-heavy sidewalks. Their presence raises questions about how pedestrians adjust their walking paths to accommodate the robots. This preliminary field study was designed to gather initial insights into these behaviors, laying the groundwork for a larger, statistically significant study to be conducted in the future.Guided by Proxemics Theory, which examines how individuals manage personal space, this study investigates pedestrian responses to Serve Robotics’ delivery robots. The research question focuses on how pedestrians modify their walking paths when encountering these robots. By documenting observable changes in pedestrian movements—such as veering, slowing down, stopping, or moving closer to the edge of the sidewalk or street—the study identifies patterns influenced by environmental factors like sidewalk width, pedestrian density, and proximity to the robot.Conducted as a preliminary observational field study, the researcher acted as a non-participant observer, documenting interactions between pedestrians and robots in real-world conditions on West Hollywood’s sidewalks. Data were collected on key behaviors, including deviations in path, stops, and speed changes in response to robot movements. Additionally, environmental factors such as time of day, weather, and pedestrian density were recorded. Video recordings, with appropriate consent signage, were used to analyze specific pedestrian behaviors and accurately measure deviations from original paths.This preliminary study utilized both quantitative and qualitative methods. The quantitative analysis specifically measured the frequency and degree of swerving, where pedestrians veered off their original walking path. It also tracked the number of stops or pauses pedestrians made in response to the robots, as well as changes in walking speed, such as slowing down or speeding up when approaching the robots. Additionally, the study recorded proximity of pedestrians to the robots, quantifying how close they allowed the robots to come before altering their path. Data were collected under various conditions, including sidewalk width (narrow versus wide) and pedestrian density (low, moderate, or high). These metrics helped identify behavioral patterns, such as whether narrower sidewalks or faster-moving robots resulted in more significant path deviations or stopping. Qualitative thematic analysis categorized pedestrian responses—such as avoidance, curiosity, or neutrality—based on observational data.Findings from this initial study provide important insights into how autonomous robots impact pedestrian traffic flow. Key behavioral trends identified in this phase of the research can inform the design of human-centered robots that navigate urban environments without causing pedestrian discomfort or creating bottlenecks. Serve Robotics and similar organizations may benefit from adjusting robot speed and proximity to pedestrians or implementing signaling mechanisms to reduce pedestrian path alterations. Insights also suggest potential municipal policies regarding where and how robots should operate on sidewalks to minimize disruptions.Initial findings underscore the need for more extensive research to develop a fuller understanding of pedestrian responses to autonomous robots. A larger study will build on the groundwork established here, aiming to help optimize the design and integration of autonomous systems into public spaces, enhancing pedestrian experiences and advancing the adoption of autonomous technologies. The findings from both this preliminary research and a future larger study will contribute significantly to the broader Human-Robot Interaction field and inform the development of robotic systems designed for more seamless interaction in real-world settings.