2010
DOI: 10.3141/2143-10
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Features that Affect Variability of Travel Time on Bus Rapid Transit Systems

Abstract: To measure the variability in end-to-end travel time, a ratio of average peak-hour travel time to the average non-peak-hour travel time was compared across BRT systems. An increase in this ratio usually comes from the effect of peak-hour traffic (2). A single end-to-end trip can be reduced to dwell time and running time. Both components of travel time can contribute to an increase in the variability of the travel time ratio.Understanding which features reduce or increase the variability of travel time is impor… Show more

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Cited by 16 publications
(8 citation statements)
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“…While stop time models are common in the literature, it is rare to find stop time variation models (20) because they are more laborious to produce (21). In other words, variation models are not common in the literature (22)(23)(24), and when they are provided, they tend to focus only on investigating running time variation by using the coefficient of variation (CV) of running time (23)(24)(25).…”
Section: Literature Reviewmentioning
confidence: 99%
See 1 more Smart Citation
“…While stop time models are common in the literature, it is rare to find stop time variation models (20) because they are more laborious to produce (21). In other words, variation models are not common in the literature (22)(23)(24), and when they are provided, they tend to focus only on investigating running time variation by using the coefficient of variation (CV) of running time (23)(24)(25).…”
Section: Literature Reviewmentioning
confidence: 99%
“…Since it is a unit free measure, it is interpreted as percentages (26). Other studies used simple descriptive statistics to understand the impact of various strategies on running time variation (21,26), without isolating different influential variables' effects on the service. However, none of the aforementioned studies have investigated the impacts of bus stop location on both stop time and stop time variation.…”
Section: Literature Reviewmentioning
confidence: 99%
“…Many researchers have investigated the effects of different strategies on running time (Diab & El-Geneidy, 2012;El-Geneidy et al, 2011;Kimpel, Strathman, Bertini, Bender, & Callas, 2005;Surprenant-Legault & El-Geneidy, 2011). Meanwhile, less attention has been given to the impacts of these strategies on the variation of service since variation is more difficult to address (Schramm, Watkins, & Rutherford, 2010). Several studies agreed that limited-stop bus service and reserved bus lane decrease running time (El-Geneidy & Surprenant-Legault, 2010;Surprenant-Legault & El-Geneidy, 2011), while TSP systems have uncertain effects on running time (Kimpel et al, 2005).…”
Section: Literature Reviewmentioning
confidence: 99%
“…They revealed that while running time had improved by 6% at the segment level, there was no evidence of any changes in running time variation, which can be associated to the length of the segment being studied. Other studies used simple descriptive statistics to understand the impact of the implementation of TSP (Kimpel et al, 2005) and to address various bus rapid transit (BRT) features on running time variation (Schramm et al, 2010), without isolating different influential variables' effects on the service. Therefore, further investigation on the effect of the use of smart cards, limited-stop bus service, articulated buses, TSP and reserved lanes on variation is required.…”
Section: Literature Reviewmentioning
confidence: 99%
“…Compared to normal bus transit (NBT), it has larger capacity, better passenger facilities such as exclusive bus lanes, fare collection system, real-time information system, and modern bus stations. It also combines advantages such as the flexibility of conventional buses and the operational efficiency of rail transit [3,4]. As a promising alternative, BRT has existed for almost 40 years, while it has not been introduced into China until the late 20th century.…”
Section: Introductionmentioning
confidence: 99%