Key points are not available for this paper at this time.
As automated vehicles become more widespread but lack a driver to communicate in uncertain situations, external communication, for example, via LEDs or displays, is evaluated. However, the concepts are mostly evaluated in simple scenarios, such as one person trying to cross in front of one automated vehicle. The traditional empirical approach fails to study the large-scale effects of these in this not-yet-real scenario. Therefore, we built PedSUMO, an enhancement to SUMO for the simulacra of automated vehicles' effects on public traffic, specifically how pedestrian attributes affect their respect for automated vehicle priority at unprioritized crossings. We explain the algorithms used and the derived parameters relevant to the crossing. We open-source our code under https://github.com/M-Colley/pedsumo and demonstrate an initial data collection and analysis of Ingolstadt, Germany.
Colley et al. (Sun,) studied this question.