Crossing Roads with a Computer-generated Agent

Abstract

This study investigated how people coordinate their decisions and actions with a risky or safe computer-generated agent in a humanoid or non-humanoid form and how this experience influences later behavior when acting alone. In Experiment 1, participants first repeatedly crossed continuous traffic in a virtual environment with a humanoid computer-generated agent (Figure 1). Participants were specifically instructed to cross with an agent that was programmed to be either safe (taking only large gaps) or risky (also taking relatively small gaps). Participants then repeatedly crossed the same roadway alone. We found that participants’ experiences with crossing safe vs. risky gaps with an agent persisted in later trials when the participants crossed alone, such that participants accepted tighter gaps if they were previously paired with a risky than a safe agent. In Experiment 2 (Figure 2), we tested whether experience crossing with a risky or safe non-humanoid object (a floating box) also influenced later behavior when crossing alone. We again found that participants who crossed with the risky object partner took tighter gaps when later crossing alone than those who crossed with the safe object partner. The Discussion focuses on the impact of experiences with virtual agents on perception–action tuning and the potential of using virtual agents for training safe road-crossing behavior.

Does another pedestrian matter? A Virtual Reality study on the interaction between multiple pedestrians and autonomous vehicles in shared space

“…This finding is in line with [38], which similarly observed that participants farther from the AV chose narrower time margins to enter the road. Overall, our findings confirmed that neighbor's behavior can impact the pedestrian's movement dynamic when crossing the road [35]. Moreover, our findings suggest that when crossing the road next to each other, two pedestrians could behave differently depending on their relative standing positions.…”

“…They concluded that clear and unambiguous communication via eHMI is crucial in situations with multiple pedestrians. In an experiment setting with traditional vehicles, [35] investigated pedestrian road crossing behavior with a risky or safe computer-generated pedestrian, [32] and [36] asked one participant to cross the road alongside a group of pedestrians in a virtual environment. However, when there are more pedestrians involved in the above-mentioned studies, they are pre-programmed computer agents, or the type of interaction is limited (e.g., clicking a button to indicate the cross-decision).…”