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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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