Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.
Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.
OCR for page 86
86 CHAPTER 8 Pedestrian LOS Model 8.1 Model Development ticipant assigned to a specific video clip. The scores were on a scale of A (best) through F (worst). For modeling purposes, Two basic forms were considered for the pedestrian LOS the letter grades were converted to numerical scores: A=1, for arterials model. The first was an aggregate model that used B=2, C=3, D=4, E=5, and F=6. the outputs from existing segment and intersection LOS Before starting correlations analysis and modeling, we cre- models to determine the arterial LOS. The other was an ated two data subsets from the overall dataset. The total agglomerate model that considered the independent charac- dataset was sorted by city and LOS grade responses. A ran- teristics of the roadway/walkway environment to calculate an dom sampling of 20% of the data representing each city and arterial LOS for pedestrians directly. Both were preliminarily LOS grade response was taken from the overall dataset for evaluated during model development. model validation. The balance of the data, 80% of the total The aggregate model was chosen for refinement for several dataset, was used for model development. reasons. The stepwise approach to an aggregate model is use- We used SPSS 14.0 to conduct Pearson correlation analysis ful because it allows the practitioner to evaluate the effect of on the extensive array of geometric and operational variables. improvements at individual intersections or along specific Subsequently, we selected the following relevant variables for segments on the overall LOS of the facility. The aggregate additional testing: model also retains all the terms found both intuitively and mathematically validated to be significant to pedestrians walk- · Segment LOS--The pedestrian LOS for roadway segments ing within an urban environment. The agglomerate models (see below). form was tested during our preliminary models and did not · Intersection LOS--The pedestrian LOS for signalized retain all the terms as significant. Consequently, we focused on intersections (see below). the aggregate model in our model development efforts. · Midblock Crossing LOS--The LOS associated with mid- We considered various functional techniques for model de- block crossings (see below). velopment, including linear regression and ordered probit. We · Total Pedestrians--The total number of pedestrians performed linear regression modeling because it is more intu- encountered in the video clip; a measure of pedestrian itive than probit modeling in practice and non-modelers better space, which is an input to the existing pedestrian LOS understand the sensitivity of the regression model. These rea- methodology in the HCM. sons are particularly important in that these models are most · Conflicts per mile--The total conflicts per mile represent frequently used: the development or analysis of specific design the motor vehicle conflicts resulting from motorists turn- options or in the development of pedestrian facility community ing across the pedestrian facility at unsignalized locations. master plans with presentations to interested citizens and pub- · Size of the city in which the data collection took place-- lic officials. To ensure the validity of the results of the linear re- The MSA population was used to represent the size of gression modeling results, we evaluated the ordered probit each city. model form as well. The results of both the linear regression and ordered probit modeling efforts are described below. The panel asked that MSA be dropped from further con- For both modeling efforts the dependent variable, sideration as a variable. Other variables were dropped from Observed pedestrian LOS, was defined as the score that a par- further consideration because of their poor correlation with