Can we enhance prosocial behavior? Using post-ride feedback to improve micromobility interactions

TL;DR

The paper tackles the challenge of promoting prosocial behavior among micromobility users to improve sidewalk interactions. It introduces a post-ride Ride Report that provides objective interaction metrics and tests its effect via a web-based Unity study with a 2×2×2 design (feedback vs no feedback; pedestrian vs robot OAs; oncoming vs crossing paths). Results show that post-ride feedback increases gap maintenance, slows approach at conflicts, and extends stopping time, indicating improved prosocial behavior, supported by both quantitative metrics and participant reflections. These findings suggest post-ride feedback can meaningfully enhance safety and social acceptance of micromobility, though future VR and in-person studies are needed to validate real-world applicability and address transparency concerns in scoring.

Abstract

Micromobility devices, such as e-scooters and delivery robots, hold promise for eco-friendly and cost-effective alternatives for future urban transportation. However, their lack of societal acceptance remains a challenge. Therefore, we must consider ways to promote prosocial behavior in micromobility interactions. We investigate how post-ride feedback can encourage the prosocial behavior of e-scooter riders while interacting with sidewalk users, including pedestrians and delivery robots. Using a web-based platform, we measure the prosocial behavior of e-scooter riders. Results found that post-ride feedback can successfully promote prosocial behavior, and objective measures indicated better gap behavior, lower speeds at interaction, and longer stopping time around other sidewalk actors. The findings of this study demonstrate the efficacy of post-ride feedback and provide a step toward designing methodologies to improve the prosocial behavior of mobility users.

Figures (8)

• Figure 1: A visual depiction of the study procedure. In the first phase of the study, the Ride Report did not occur; however, all other elements were identical.
• Figure 2: An example of the post-ride feedback, or Ride Report, displayed to the participants.
• Figure 3: Scores calculation for the ride report in a given trial. Sample values show the score calculation for a participant in Route 4.
• Figure 4: Trend of scores across trials for the feedback and no-feedback group participants.
• Figure 5: Trends of minimum gap metric across the trials for feedback group and no-feedback group participants.