An appropriate spatial resolution plays a significant role in any travel demand models. It directly impacts the level of detail of model input data, outcomes, and sensitivities (Castiglione et al., 2014; Moeckel and Donnelly, 2015). Compared to motorized or bicycle travel, pedestrian trips occur over a shorter travel distance and they are sensitive to environmental conditions at a much finer grain. Thus, it is important for models to set an appropriate spatial resolution to capture variations in walking conditions, leading to better representation of pedestrian demand over space (Gehrke and Clifton, 2014). The model of pedestrian demand (MoPeD) developed by Dr. Clifton’s team integrates pedestrians into urban trip- based travel models for the Portland metropolitan area (Clifton et al., 2016a). It changes the spatial unit from Transportation Analysis Zone (TAZ) to a finer spatial scale called Pedestrian Analysis Zone (PAZ) defined by an 80m×80m grid cell and an aggregation of these PAZs into 400m x 400m zones called a superPAZ. Compared to the TAZs (Figure 1), PAZs can better represent pedestrian behavior and react to the changing pedestrian environment, but they also escalate computational burden, particularly in the destination choice step. Although the current complexity of models remain, particularly for applying MoPeD to a large-scaled study area or to a large number of scenarios.     «

An appropriate spatial resolution plays a significant role in any travel demand models. It directly impacts the level of detail of model input data, outcomes, and sensitivities (Castiglione et al., 2014; Moeckel and Donnelly, 2015). Compared to motorized or bicycle travel, pedestrian trips occur over a shorter travel distance and they are sensitive to environmental conditions at a much finer grain. Thus, it is important for models to set an appropriate spatial resolution to capture variatio...     »