Virtual immersive reality for stated preference travel behavior experiments: A case study of autonomous vehicles on urban roads

Farooq, Bilal; Cherchi, Elisabetta; Sobhani, Anae · 2018 · Transportation Research Record

DOI: 10.1177/0361198118776810

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Summary

This paper addresses the lack of realism in Stated Preference (SP) experiments, a critical limitation when assessing public acceptance of novel technologies like Connected and Autonomous Vehicles (CAVs). Traditional SP surveys, often text-based or using simple visual aids, rely on respondents’ limited mental images of unfamiliar technologies, leading to heterogeneous understanding and potential bias. To mitigate this, the authors introduce the Virtual Immersive Reality Environment (VIRE), a platform designed to create highly realistic, interactive, and immersive choice scenarios. The study demonstrates VIRE’s utility by investigating pedestrian preferences regarding autonomous vehicles and associated infrastructure changes on urban roads. The VIRE platform integrates four systems: Scenario Development using the Unity gaming engine; Multi-Modal Traffic Micro-Simulation employing the Intelligent Driver Model for vehicles and social force models for pedestrians and cyclists; Virtual Environment Projection via Head-Mounted Displays (HMDs) like the Oculus Rift; and Response Tracking, which records trajectory, head orientation, and vocal reactions. The experimental design involved 42 respondents in Montréal and Toronto who evaluated two scenarios: a current state with signalized intersections and human-driven vehicles, and a hypothetical scenario with unsignalized intersections, autonomous vehicles, and pedestrian priority. Participants experienced these scenarios through three methods: text-only descriptions, visual animations, and the immersive VIRE environment. In the VIRE trials, respondents physically walked through the virtual intersection, with vehicle arrivals controlled by a Poisson distribution. The results indicate that VIRE significantly improves scenario understanding and yields more consistent preference data compared to traditional methods. While only 50% of respondents preferred the autonomous vehicle scenario in the text-only condition, this preference dropped below 40% with visual animations but rose to 70% in the VIRE environment. Gender differences were pronounced; female respondents were generally more conservative, preferring the current state in text and visual conditions, but their preference flipped to favor autonomous vehicles when using VIRE. Multinomial Logit models confirmed that the VIRE-based model had superior statistical fit and a different scale parameter, indicating higher data quality. Factors such as age, gender, primary travel mode, and prior HMD experience significantly influenced preferences, with millennials and those familiar with VR showing greater acceptance of autonomous vehicles. The study concludes that VIRE effectively addresses the realism deficit in SP experiments, particularly for disruptive technologies lacking a clear reference point in daily life. By providing direct experience and capturing rich behavioral data without additional respondent burden, VIRE enables more accurate modeling of travel behavior. The authors suggest that this approach can facilitate the investigation of complex mental processes and plan to expand the platform to include manual driving simulations and multi-user interactions, aiming to lower barriers for broader adoption in transportation research.

Key finding

Using a virtual immersive reality environment for stated preference experiments significantly increased pedestrian acceptance of autonomous vehicles and produced more consistent behavioral data compared to text-only or visual animation methods.

Methodology

lab_experiment

Sample size: 42

Provenance

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Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.

Topics

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• acceptance adoption