Application of New Pedestrian Level of Service Measures - sacog

3. Literature Review of Existing
Analysis Tools
In the literature review, staff looked at level of service, accessibility, and walkability
analyses. Exhibit B below provides a brief description of each of the sources considered.
Reflective of the complex nature of the pedestrian environment, the sources often covered
multiple factors to varying extents, including:
qualitative elements (e.g. perceived comfort, safety)
land uses (e.g. destinations, frontage, block ratios)
engagement (e.g. schools, communities, local agencies)
transit access (e.g. stops, frequency)
facilities present or absent (e.g. sidewalks, amenities)
roadway characteristics (e.g. traffic volume, number of lanes)
However, the focus of this project is to recognize factors that can be evaluated in SACOG’s I‐
PLACE 3 S model and quantitative, measurable, transportation‐related elements were
considered in each model (Exhibit C).
Selection of Models for Use in Pedestrian Level of Service Analysis
After reviewing the literature, we selected two models to evaluate the case study areas.
We selected two pedestrian LOS models because we felt that the models that considered
surrounding land uses (walkability models) were too subjective or did not appropriately
address the physical pedestrian infrastructure. We also felt that by selecting two models
that both assessed pedestrian LOS we would better be able to identify common factors and
draw better conclusions from the results of the analysis. Finally, by selecting two pedestrian
LOS models, the data collection process was simplified and expedited. However, we do
recognize the importance of walkability measures, and future study related to walkability is
something that could further inform SACOG’s I‐PLACE 3 S software and SACOG’s travel
demand forecasting programs. This idea is discussed further in Section 7. Conclusions.
Although these models are both pedestrian LOS models, they were selected for very
different reasons. The Multi‐Modal Level of Service (MMLOS) model (source “m” in Exhibits
B and C) was selected because of the breadth of factors it considers, its outstanding
supporting documentation, and its wide use in traffic analyses at the local level.
The Pedestrian Performance Measure (PPM) model (source “n” in Exhibits B and C) was
selected because its simple, point‐based system is more accessible to non‐technical staff
and can be customized to include or exclude certain factors. While not as detailed as the
MMLOS model, this model captures many of the most important factors that affect
pedestrian LOS.
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