Ranking Crossing Scenario Complexity for eHMIs Testing: A Virtual Reality Study

Abstract

External human–machine interfaces (eHMIs) have the potential to benefit AV–pedestrian interactions. The majority of studies investigating eHMIs have used relatively simple traffic environments, i.e., a single pedestrian crossing in front of a single eHMI on a one-lane straight road. While this approach has proved to be efficient in providing an initial understanding of how pedestrians respond to eHMIs, it over-simplifies interactions which will be substantially more complex in real-life circumstances. A process is illustrated in a small-scale study (N = 10) to rank different crossing scenarios by level of complexity. Traffic scenarios were first developed for varying traffic density, visual complexity of the road scene, road geometry, weather and visibility conditions, and presence of distractions. These factors have been previously shown to increase difficulty and riskiness of the crossing task. The scenarios were then tested in a motion-based, virtual reality environment. Pedestrians’ perceived workload and objective crossing behaviour were measured as indirect indicators of the level of complexity of the crossing scenario. Sense of presence and simulator sickness were also recorded as a measure of the ecological validity of the virtual environment. The results indicated that some crossing scenarios were more taxing for pedestrians than others, such as those with road geometries where traffic approached from multiple directions. Further, the presence scores showed that the virtual environments experienced were found to be realistic. This paper concludes by proposing a “complex” environment to test eHMIs under more challenging crossing circumstances.