| Abstract |
Cycling plays an important role in improving mobility, health, and sustainability; however, designing attractive and usable bicycle infrastructure requires a clear understanding of users’ preferences and perceptions. Achieving this understanding often demands substantial financial resources, robust methodologies, and considerable research effort. Existing approaches—including surveys, naturalistic observations, and field experiments—provide valuable insights but are frequently constrained by hypothetical bias, high costs, long implementation timelines, safety risks, limited applicability to unbuilt infrastructure, and reduced replicability.
Virtual reality (VR) has emerged as a promising methodological tool for addressing these limitations by offering a cost-effective and scalable means of evaluating cyclists’ perceptions of existing and proposed bicycle infrastructure within controlled yet immersive environments. VR-based approaches support early-stage assessment of design alternatives while enabling the collection of behavioral, perceptual, and physiological responses without exposing participants to real-world risk. Importantly, VR environments allow diverse user groups (e.g., children, less-experienced cyclists) to safely test and experience infrastructure designs, supporting more inclusive, capabilities-centred planning processes.
This presentation will showcase an inclusive, immersive, and replicable VR-based bicycling simulator for infrastructure planning and behavioral perception analysis. The proposed framework outlines the development of a high-fidelity virtual cycling laboratory using commercially available bicycle trainers, sensors, and the Unity game engine to replicate real-world cycling contexts. The methodology enables the integration of physiological health data (e.g., eye-tracking, heart rate, and physical movement measures such as leaning, braking, and turning). These data support a detailed examination of how different infrastructure configurations influence real-time health indicators, along with perceived safety, comfort, and usability.
The intellectual contribution of this work lies in advancing realism-driven methods for active transportation research through the systematic integration of behavioral, physiological, and perceptual
data within a human-centred simulation framework. Practically, the proposed approach offers planners, engineers, and policymakers a scalable and cost-effective tool to evaluate bicycle infrastructure designs before implementation. Beyond the case study context, the framework can be adapted by other municipalities and communities to support inclusive, evidence-based, and community-informed cycling infrastructure planning, contributing to more equitable, healthy, and sustainable transportation systems.
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