2019
DOI: 10.1080/19427867.2019.1665774
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Effect of on-ramp demand and flow distribution on capacity at merge bottleneck locations

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Cited by 9 publications
(3 citation statements)
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“…However, the omission or shortening of auxiliary lanes does not appear to significantly affect operational efficiency in certain conditions [32]. The detrimental impact of overflow traffic from ramps on the capacity in merging areas has also been established, suggesting a correlation between the number of lanes and capacity bottlenecks [33], [34]. These studies provide important references and inspiration for the design of three-lane ramps.…”
Section: Introductionmentioning
confidence: 79%
“…However, the omission or shortening of auxiliary lanes does not appear to significantly affect operational efficiency in certain conditions [32]. The detrimental impact of overflow traffic from ramps on the capacity in merging areas has also been established, suggesting a correlation between the number of lanes and capacity bottlenecks [33], [34]. These studies provide important references and inspiration for the design of three-lane ramps.…”
Section: Introductionmentioning
confidence: 79%
“…Previous studies indicated that the traffic conditions of a highway network were greatly affected by the traffic conditions of several key bottleneck segments [31][32][33]. Consequently, improving the traffic conditions of the bottleneck segments was regarded as a feasible and effective way of enhancing the transportation efficiency of a highway network [34,35].…”
Section: Literature Reviewmentioning
confidence: 99%
“…Multivariate linear regression is a tool used to obtain the importance that each independent variable imposes to obtain a predictive model of the dependent variable [87]. Researchers have used regression to evaluate the relationship between drivers' physiological responses, situational factors and takeover request lead time in a simulated driving environment [88], to estimate pavement condition indices as a function of the International Roughness Index (IRI) and the Pavement Condition Index (PCI) [89], to predict annual average daily trac function of road, land use and demographic and socioeconomic characteristics [90,91] and to explore the relationship between on-ramp ow and capacity [92]. In terms of regression models, the most used is linear regression and one of the methods that can be adopted is stepwise.…”
Section: Literature Reviewmentioning
confidence: 99%