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NCHRP Report 616: Multimodal Level of Service Analysis for Urban Streets (2008)
National Cooperative Highway Research Program (NCHRP)

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Flannery, Aimee, Dowling, Richard G, Rouphail, Nagui M, Petritsch, Theodore Anton, Landis, Bruce W, Bonneson, James A, Ryus, Paul, Reinke, David B, Vandehey, Mark, Transportation Research Board. "Rural Road Research." NCHRP Report 616: Multimodal Level of Service Analysis for Urban Streets. Washington, DC: The National Academies Press, 2008.

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Front Matter (R1-R11)
Summary (1-2)
1.2 The Research Plan (3-3)
1.3 This Report (4-4)
Highway Capacity Manual (5-5)
Transit Capacity and Quality of Service Manual (6-8)
Florida Quality/Level of Service Handbook (9-10)
Highway Capacity Manual (11-12)
Transit TCQSM Critique (13-13)
Florida DOT Q/LOS Handbook (14-14)
The Major Level of Service Manuals (15-15)
Implications for Research Project (16-16)
Urban Street LOS (17-17)
Intersection LOS Research (18-20)
Rural Road Research (21-21)
A Handbook for Measuring Customer Satisfaction (22-22)
3.3 Bicyclist Perceptions of LOS (23-23)
Segment LOS Models Based on Field Surveys or Video Lab (24-25)
Models of Rural Road Bicycle LOS (26-26)
Intersection Crossing LOS Studies (27-27)
Sidewalk and Path LOS Studies (28-28)
Midblock Crossing LOS Studies (29-29)
3.5 Multimodal LOS Research (30-31)
4.1 Selection of QOS Survey Method (32-34)
Auto Video Clips (35-35)
Bicycle Video Clips (36-37)
Pedestrian Video Clips (38-41)
Development of Master DVDs (42-45)
Selection of Video Lab Cities (46-46)
Recruitment (47-49)
Video Lab Sessions (50-50)
4.5 Effects of Demographics on LOS (51-51)
Effects of Demographics on Auto LOS Ratings (52-52)
Effects of Demographics on Pedestrian LOS Ratings (53-53)
Field Data Collection (54-54)
Survey Form Development (55-56)
Survey Distribution (57-57)
Route Characteristics (58-59)
4.7 Representation of Survey Results By A Single LOS Grade (60-61)
Linear Regression Tests (62-63)
Limitations of Linear Regression Modeling (64-64)
Performance of Candidates (65-68)
5.2 Recommended Auto LOS Model (69-70)
5.3 Performance of Auto LOS Models (71-71)
Selection of Explanatory Variables for LOS (72-73)
Elasticity Concept (74-76)
Reliability (77-77)
6.2 Recommended Transit LOS Model (78-78)
Estimation of the Transit Wait Ride Score (79-80)
6.3 Performance of Transit LOS Model (81-81)
7.2 Recommended Bicycle LOS Model (82-82)
Bicycle Intersection LOS (83-83)
7.3 Performance of Bicycle LOS Model on Video Clips (84-85)
8.1 Model Development (86-86)
Pedestrian Other LOS Model (87-87)
Pedestrian Midblock Crossing Factor (88-90)
8.3 Performance Evaluation of Pedestrian LOS Model (91-91)
Input Variable Interactions Among Modes (92-94)
Interactions Among Modal LOS Results (95-95)
Chapter 10 - Accomplishment of Research Objectives (96-97)
References (98-101)
Appendix A - Subject Data Collection Forms (102-104)
Appendix B - Study Protocol (105-109)
Appendix C - Example Recruitment Flyer/Poster (110-110)
Abbreviations used without definitions in TRB publications (111-111)

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21 letter-grade level of service is then determined from a hazard participants (in groups of 7 to 10) a tape of a series of signal- index look-up table. ized intersections. The intersections portrayed on the tape Zhang and Prevedouros [17] developed a model of were chosen in cities outside the local area to eliminate fa- vehicle-to-vehicle and vehicle-to-pedestrian conflicts and miliarity by the subjects, but in a location nearby so that local blended it with the existing HCM delay LOS criteria for sig- conditions were represented. The results of the study showed nalized intersections to obtain an LOS model that combines that, on average, subjects' delay estimates were fairly accurate, safety risk with traditional delay measures of LOS. Two delay but widely variable on an individual basis. The study also and safety indices are computed--one for pedestrians, the showed that subjects perceived three or four levels and were other for vehicles. Each index is computed as a weighted sum more tolerant of delays than suggested by the HCM. At least of potential conflicts and delay. The weights are analyst spec- 15 factors emerged from the group discussions that subjects ified. The two indices are then weighted by pedestrian and ve- identified as influential in their LOS ratings. These included hicle volumes, respectively, to obtain a weighted average delay, traffic signal efficiency, arrows/lanes for turning vehi- delay and safety index for the intersection. No surveys of cles, clear/legible signs and road markings, geometric design traveler perception were performed. This paper was oriented of intersection, leading left-turn phasing scheme, visual toward methodological approaches rather than traveler clutter/distractions, size of intersection, pavement quality, perception. queue length, traffic mix, location, scenery/aesthetics, and Several recent studies of intersection LOS have also cast presence of pedestrians. some doubt on the HCM's methods. Zhang and Prevedouros (2004) [18] investigated motorists' perceptions of LOS at case Use of Fuzzy Logic for LOS Modeling study signalized intersections and found that, although the HCM 2000 predicts that permitted left-turn phases provide a Recent research has begun to use "fuzzy logic" to identify higher level of service, users ranked protected left-turn delay thresholds for rating the level of service of signalized phased intersections higher. This finding suggests that users intersections. may be including the perceived safety benefits of protected Fang and Pecheux [22] conducted a video laboratory of phasing at these case study locations in their assessments of 98 subjects assessing the quality of service on 24 signalized in- LOS, in addition to delay. In a follow-up study, Zhang and tersection approaches. Cluster analysis (employing fuzzy Prevedouros (2005) [19] surveyed users' perceptions of ser- thresholds) revealed that their subjects' quality of service as- vice quality at intersections and found that users consider sessments did not distinguish between the delays at HCM multiple factors beyond delay (as calculated by the HCM LOS A or B. The LOS ratings of their subjects, however, did 2000), including signal efficiency, left-turn treatment, and distinguish two classes of delay for delays at HCM LOS F. pavement conditions. Delay scored relatively low among im- Zhang and Prevedouros [23] conducted a web-based portant factors. Drivers prefer to make left turns under pro- stated preference survey of 1,300 volunteers. Their survey tected left-turn signals, especially at large intersections. Safety identified delay, pavement markings, presence of exclusive was stated to be 3 to 6 times more important than delay, de- left-turn lanes, and protected left-turn phases, as factors sig- pending on the type of conflict. nificantly affecting the perceived level of service at a signal- The importance of safety in determining the level of service ized intersection. Fuzzy inference was used to identify a offered by an intersection is reflected in a study by Li et al. distribution of LOS responses for a given physical condition. (2004) [20]. Li et al. used a "gray system" theory-based A percent confidence level was then reported for each LOS method to rank and evaluate the operational and safety letter grade. performance of signalized intersections in mixed traffic con- Lee, Kim, and Pietrucha [24] exposed 27 subjects to video ditions. The degree of saturation, average stopped delay, clips of 12 signalized intersections. Subjects were asked to queue length, conflict ratio, and separation ratio are all used (1) rate their intersection experience as "poor," "acceptable," or as parameters. Results of application in the urban area of "good" and (2) describe the relative importance of six criteria Changsha, China, show that the method can be used to con- to their rating of the intersections. The six criteria evaluated duct a comprehensive (safety and operations) performance were delay, gaps in cross street traffic while waiting, efficiency under mixed traffic conditions. of traffic signal operation, visibility of signal, signing/markings, Pecheux, Pietrucha, and Jovanis [21] addressed users' per- and physical features of the intersection. ception of level of service at signalized intersections. The re- search objectives were to examine delay distributions, assess Rural Road Research the accuracy of delay estimates, determine if current levels of service are appropriate, and identify factors affecting per- Nakamura, Suzuki, and Ryu [25] conducted a field driving ceptions. The research used a video laboratory to show 100 survey on a rural motorway section under uncongested traffic