Default Values for Highway Capacity and Level-of-Service Analyses

Zegeer, John; Blogg, Miranda; Nguyen, Khang; Vandehey, Mark

doi:10.3141/2071-05

Cited by 20 publications

(7 citation statements)

References 4 publications

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“…This Florida Department of Transportation method is limited to undersaturated conditions and does not model queuing and congested freeways in a planning context. Broader national guidance on the use of default values from the HCM is provided in NCHRP Report 599, but without specific methodology (9).…”

Section: Literature Reviewmentioning

confidence: 99%

Planning-Level Methodology for Freeway Facilities

Hajbabaie

Rouphail

Schroeder³

et al. 2015

Transportation Research Record

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This paper presents a planning-level methodology for the analysis of freeway facilities. The proposed approach is based on and compatible with the operational method of the Highway Capacity Manual 2010 (HCM 2010). The approach is specifically constructed with the intent to minimize input data requirements. The method covers both under- and oversaturated flow conditions and produces estimates of travel time, speed, density, and level of service. The underlying methodology relies on developing a relationship between a basic freeway segment's delay rate per unit distance and its demand-to-capacity ratio. For weaving segments, the study develops capacity adjustment factors on the basis of volume ratio and segment length. With these factors, demand-to-capacity ratios on weave segments were adjusted and the segment was treated similarly to a basic freeway segment. For merge and diverge segments, a novel methodology is proposed to estimate their capacity on the basis of demand level, free-flow speed, and space mean speed. Subsequently, capacity adjustment factors are calculated on those segments and their demand-to-capacity ratios are adjusted accordingly. The proposed approach is applied to two examples in the HCM 2010 and produced very promising results. For undersaturated flow conditions, facility travel time is at most 3.4% and density was at most 1.1% at variance from the results found by applying the HCM 2010 operational methodology. The corresponding differences for oversaturated conditions are 6.7% and 13.0%, respectively.

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Section: Literature Reviewmentioning

confidence: 99%

Planning-Level Methodology for Freeway Facilities

Hajbabaie

Rouphail

Schroeder³

et al. 2015

Transportation Research Record

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“…This study considered only the uncertainty in the heavy vehicle volumes, which is caused by the difficulty of quantifying effects of region and area populations on demand (28). The passenger car equivalent value of trucks was assumed to be a constant value of 1.5 for this analysis and was taken from the HCM 2010 for level terrain.…”

Section: Heavy-vehicle Adjustment Factormentioning

confidence: 99%

Reliability-Based Geometric Design Approach for Selecting Basic Number of Freeway Lanes

Musunuru

Porter

2014

Transportation Research Record

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Reliability-based geometric design analysis is more suitable for explicitly addressing the level of variability and randomness associated with design inputs than is a more deterministic design approach. Reliability analysis was used to estimate the probability distribution of operational performance that might result from basic decisions made to achieve a design level of service (LOS) for number of lanes on a freeway. The concept was demonstrated with data from I-15 and I-80 in Utah. To account for uncertainty in the design inputs, statistical distributions were developed, and reliability analysis was carried out with Monte Carlo simulation. The outcome of this probabilistic analysis was a distribution of vehicle density for a given number of lanes during the design hour. The main benefit of reliability analysis is that it enables designers to explicitly consider uncertainties in their decision making and to illustrate specific values of the distributions that correspond with the target LOS (e.g., the 65th through 85th percentile density levels correspond to those in the design LOS). The results demonstrate how uncertainty in estimates of the percentage of daily traffic in the design hour, the directional distribution, the percentage of heavy vehicles, and the free-flow speed significantly contribute to variation in vehicle density on a freeway.

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“…Unfortunately, the problem of how to relate the bicycle traffic to motorized vehicle flow harmoniously, especially within the intersection location, has remained unsolved. Since the conflicting vehicle flows that bicyclists encounter at signalized intersections change periodically and a large quantity of them has no respect toward traffic signals, it is difficult to estimate the capacity of bicycle flow through a HCM based model under mixed traffic environment [20]. In this project, therefore, a total of 4 typical signalized intersections in Xi'an with varying motor and bicycle traffic volumes were videotaped for a total of approximately 2 hours (7:30 AM to 8:30 AM and 5:30 PM to 6:30 PM) so as to achieve the traffic flow data from signalized intersections.…”

Section: Introductionmentioning

confidence: 99%