Mixed-Priority Pedestrian Delay Models at Single-Lane Roundabouts.

This paper presents an approach for developing pedestrian delay models atsingle-lane roundabouts using behavioral crossing data. The models use probabilistic behavioral parameters measured in controlled pedestrian crossings by blind pedestrians as part of NCHRP project 3-78a. While blind pedestrians clearly represent a special population of pedestrians, the developed delay model is structured to be applicable to all populations. Delay is predicted as a function of the probability of encountering a crossing opportunity in the form of a yield or crossable gap, and the probability of utilizing that opportunity, which are aggregate to an overall probability ofcrossing. Models are developed from a dataset of three different single-lane US roundabouts and a total of 40 independent study participants. The paper presents the theoretical approach to estimating the probability parameters and uses a multi-linear log-transformed regression approach to predict the average pedestrian delay. Special consideration is given to the first opportunity delay, recognizing that many blind pedestrians may miss or reject some opportunities. By setting opportunity utilization rates equal to 1.0, the model can approximate general pedestrian crossing performance.The final delay model explains 64% of the variability in the observed data and therefore represents a reasonable model for predicting the delay at single-lane roundabouts. The paper concludes with a discussion of how agencies can estimate the underlying probability parameters for existing or proposed roundabouts using empirical and theoretical approaches, and how pedestrian crossing treatments can be used in the context of the model to reduce average pedestrian delay. The research is important in light of the ongoing debate of the accessibility of modern roundabouts to pedestrians whoare blind. However, the results have further application to the general evaluation of pedestrian facilities at roundabouts, an application where existing Highway Capacity Manual methods are limited. The probabilistic approach to predicting pedestrian delay is universal and can be applied other pedestrian populations with the right probability parameters. Calibration to other crossing geometries is feasible with future data collection.