Multimodal Level of Service Analysis for Urban Streets (2008) / Chapter Skim
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From page 17... ...
and video laboratories and have laboratory interviews to identify key factors affecting perceived LOS and to obtain LOS ratings for different field conditions. Level of service has been defined by researchers in various ways.
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From page 18... ...
The proposed MOEs reflect the input provided by the participants in the study, but combine like QOS factors into, for the most part, measurable performance measures. For example, participants in the study often commented negatively when they were forced to slow down or stop because of poor arterial design that did not provide for bus pullouts, turning facilities, on-street parking maneuvers, and poor access management that created many merge/diverge situations.
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From page 19... ...
MOEs QOS Factors Number of stops Turning lanes/bays Bus pull-out areas On-street parking Two-way center left-turn lane Access management Lane drop/add Urban street capacity Heavy vehicles Lane width Number of lanes/roadway width Intersection efficiency Signal timing (cycle length/cycle split) Provision for turning vehicles Urban street efficiency Progression Number of traffic signals Travel time Travel speed Traffic volume Volume/congestion Traffic flow Speed Travel time Positive guidance Quality of pavement markings Sign legibility/visibility Sign presence/usefulness Lane guidance -- signs Lane guidance -- pavement markings Advance signing Too many signs (clutter/distracting)
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From page 20... ...
Based on the findings of this single research study, the Highway Capacity and Quality of Service Committee overhauled the 1985 HCM to represent level of service at signalized intersections by AID versus LF. The authors state, "Field studies and the attitude survey provided data for the development of two psychophysical models.
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From page 21... ...
These included delay, traffic signal efficiency, arrows/lanes for turning vehicles, clear/legible signs and road markings, geometric design of intersection, leading left-turn phasing scheme, visual clutter/distractions, size of intersection, pavement quality, queue length, traffic mix, location, scenery/aesthetics, and presence of pedestrians. Use of Fuzzy Logic for LOS Modeling Recent research has begun to use "fuzzy logic" to identify delay thresholds for rating the level of service of signalized intersections.
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From page 22... ...
Twenty-four participants drove subject vehicles in both directions in the study segment for a total of 105 test runs. Videocameras were mounted on the test vehicle to record travel time, number of lane changes, time of a car-following situation by lane, and elapsed travel time by lane.
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From page 23... ...
The authors also found that the activity center selection method resulted in work ends of trips being over-represented and home ends of trips being under-represented There were also various issues with the difficulty and cost of data collection (e.g., the validity of mixing field data on passenger loads and transit travel times with model estimates of travel times and demand for the computation of some of the level of service measures)
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From page 24... ...
Cumulative logit model forms were selected for both the bicycle and pedestrian LOS models. These models predicted the percentage of responses for each of the 6 levels of service.
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The percentage of trucks ranged from zero to 8.1. The posted speed limits ranged from 25 to 55 mph.
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From page 26... ...
In the end, eight variables were found to be significant in the BCI regression model: • Number of lanes and direction of travel; • Curb lane, bicycle lane, paved shoulder, parking lane, and gutter pan widths; • Traffic volume; • Speed limit and 85 percentile speed; • Median type (including two-way left turn lane) ; • Driveway density; • Presence of sidewalks; and • Type of roadside development.
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From page 27... ...
3.4 Pedestrian Perceptions of LOS Researchers have used field intercept surveys and closed course surveys in the field to measure pedestrian perceptions of level of service. Some distributed questionnaires in the field to be returned later via the mail.
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Analysis of the results of these studies suggests that the most important variables that determine pedestrian LOS -- and therefore, the very definition of pedestrian LOS itself -- change depending on the context. As described in more detail under the bicycle LOS model section, Jensen [50]
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From page 29... ...
The resulting equation had an R-square value of 85%, but later researchers have noted that this value was for the ability of the model to predict the average LOS for a segment, not the actual LOS values reported by each individual participant. Human factors are completely absent from the pedestrian LOS model.
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From page 30... ...
Some, like FDOT's bicycle and pedestrian LOS measures are based on travelers' perception of safety, which is a higher priority need than "convenience" which is implicit in the auto LOS measure of speed. They suggested offsetting the scales against some standard of traveler satisfaction, i.e., using a sliding scale.
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From page 31... ...
Pedestrian LOS depends on sidewalk presence, roadway widths, separation from traffic, and vehicle speeds and volumes. Transit LOS depends on service frequency, adjusted for pedestrian LOS and hours of service per day.
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