Application of New Pedestrian Level of Service Measures - sacog
Application of New Pedestrian Level of Service Measures - sacog
Application of New Pedestrian Level of Service Measures - sacog
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<strong>Application</strong> <strong>of</strong> <strong>New</strong> <strong>Pedestrian</strong> <strong>Level</strong> <strong>of</strong> <strong>Service</strong> <strong>Measures</strong><br />
SACOG<br />
7. Conclusions<br />
Critical Factors in Evaluating <strong>Pedestrian</strong> LOS<br />
Although both models had very different approaches to quantifying pedestrian LOS, there<br />
were several common factors that both models weighted heavily in the scoring. These<br />
factors include:<br />
Presence and condition <strong>of</strong> sidewalks<br />
Buffers between vehicular traffic and pedestrian traffic<br />
Posted speed limit<br />
Number <strong>of</strong> lanes<br />
Traffic volumes<br />
Few conflicts with other modes<br />
Considerations for Using the MMLOS and PPM Models for Future Analysis<br />
Factors Considered and Data Needs<br />
The MMLOS model is very detailed and considers many factors; however, that level <strong>of</strong> detail<br />
requires intensive data collection that not all agencies have the resources to undertake. The<br />
MMLOS model is more suited to traffic engineers doing analysis for a specific project, where<br />
only a small portion <strong>of</strong> a street is being considered. The amount <strong>of</strong> effort necessary to<br />
evaluate entire corridors, neighborhoods, or cities is likely prohibitive, especially for smaller<br />
agencies.<br />
Complexity<br />
In addition to needing large quantities <strong>of</strong> data, the MMLOS model is complex. Casual users<br />
would be hard‐pressed to understand the relationships between variables. Again, for traffic<br />
engineers who work with these types <strong>of</strong> data frequently, this model would be a useful tool.<br />
For advocates and planners, however, the MMLOS model may not be a good fit for<br />
performing corridor and neighborhood analyses.<br />
Additionally, the MMLOS model is not readily customizable and takes a great deal <strong>of</strong><br />
tweaking to account for varying treatments on roadways. For example, the version <strong>of</strong> the<br />
model used in this study was set up to analyze signalized intersections. This is acceptable on<br />
busy urban and suburban arterials where nearly every intersection is signalized, but it does<br />
not work as well in small downtown areas or residential neighborhoods. The MMLOS<br />
technical background documents and the Highway Capacity Manual outline modifications<br />
that would account for different roadway treatments, but that analysis is beyond the scope<br />
<strong>of</strong> this project.<br />
Consideration <strong>of</strong> Traffic Volume<br />
Average daily traffic (ADT) is the most heavily weighted factor in the MMLOS model. Even<br />
segments with relatively moderate traffic volumes (8,000‐14,000 ADT) will find it difficult to<br />
score above average LOS. Only segments with very low volumes (4,000‐6,000) scored well in<br />
the MMLOS model analysis. The PPM model, on the other hand, assigns points based on<br />
automobile LOS rather than separating out traffic volumes, number or lanes, and congestion<br />
Issue Date: June 2011<br />
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