High volume bus stop upstream average waiting time for working capacity and quality of service

Bunker, Jonathan M.

doi:10.1007/s12469-018-0179-1

Cited by 18 publications

(22 citation statements)

References 10 publications

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“…However, considerable time and effort is required to use pedestrian microscopic simulation software to model a platform, and the user must be educated about the theoretical constructions and assumptions behind the software. According to Bunker ( 2018 ), when using microscopic simulation software to study the capacity and QoS of BRT systems, it is not easy to control every parameter in the simulation model. Therefore, the need remains for a deterministic model that can be used to analyse the complex operation of transit platforms.…”

Section: Literature Reviewmentioning

confidence: 99%

Time–space analysis to evaluate cell-based quality of service in bus rapid transit station platforms through passenger-specific area

et al. 2021

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It is important to evaluate the quality of service (QoS) of bus rapid transit (BRT) station platform operation. Passenger-specific area (PSA) is used as a QoS measure which is determined by considering passenger activities separately. As passengers perform various activities on the same platform space, there is a need to evaluate BRT platform QoS by considering the activities collectively. When evaluating transit station platforms, many researchers calculated PSA for the whole platform area, while very few researchers highlighted the importance of evaluating the platform as small, partitioned areas. By considering these findings and gaps in the literature, this study evaluates QoS of the platform on a cell by cell basis using PSA. We use time–space analysis and passenger-minutes of each activity to develop a methodology to determine PSA, by considering stationary passengers, circulating passengers, and passengers overall. To evaluate platform QoS, we define threshold service levels using passenger-minutes of activities and Fruin’s QoS criteria. For the case study BRT station, we find that PSA varies significantly between platform cells. It is evident from the results that it is important to identify highly congested areas in the platform and apply measures to improve platform QoS.

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Section: Literature Reviewmentioning

confidence: 99%

Time–space analysis to evaluate cell-based quality of service in bus rapid transit station platforms through passenger-specific area

et al. 2021

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“…This will be investigated in future research. This will include how adoption of a maximum working degree of saturation for a loading area, either by application of an operating margin or by setting a limit on bus approach average delay, according to the method developed by Bunker ( 21 ), may ameliorate such a phenomenon.…”

Section: Bcal Model and Aimsun Simulation Model Comparisonmentioning

confidence: 99%

Capacity Estimation of On-Street, Mid-Block, Off-Line Bus Stops Considering Yield-to-Bus Rule

Hisham

Bunker

Bhaskar

2019

Transportation Research Record: Journal of the Transportation R

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The effectiveness of an on-street bus facility depends on the volume of general traffic sharing the buses’ travel lane. The Transit Capacity and Quality of Service Manual (TCQSM) methodology estimates capacity of a bus facility based on the operation of critical stops. The aim of this study is to understand better the performance of an on-street, mid-block, off-line bus stop by relating bus stop capacity to adjacent lane traffic volume. The contributions of this paper are twofold. First, the TCQSM methodology incorporates the effect of adjacent lane traffic volume on bus stop capacity at mid-block bus stops through its effect on re-entry delay, but it does not consider the impact of the bus stop itself on adjacent lane traffic capacity. This paper introduces a novel methodology to estimate the additional time required to accommodate adjacent lane traffic volume under saturated conditions. Second, the TCQSM methodology does not reflect the effect on re-entry delay of a yield-to-bus (YTB) rule, which is mandatory by law in some jurisdictions. This paper modifies the current TCQSM methodology by allowing for the YTB rule. A microscopic simulation model is developed in order to cross-validate the theoretical model developed.

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“…BRT service satisfaction is achieved by increasing service procedures, service requirements, and service distinction with conventional public transportation [3]. The quality of service is measured by customer experiences through maintaining bus stop average waiting time, evaluating the impact of operation timetable, and considering BRT capacity [4].…”

Section: Introductionmentioning

confidence: 99%

Non-Ridership Presumption Toward New Bus Rapid Transit Purwokerto-Purbalingga Execution

Romadlon¹

2020

Adv. sci. technol. eng. syst. j.

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Purbalingga is a new mass transportation mode. Recently, the execution of the BRT has been going on for three years. In terms of service standards to ridership, the BRT has been fulfilled the requirement. However, during the execution, it shall be supported by the non-ridership (local communities) who get the impact as public engagement. The non-ridership impact is captured by observing their presumptions. This study uses quantitative method and survey technique to collect the data by spreading questionnaires to the non-ridership in Purwokerto and Purbalingga. The collected data is analyzed by Analysis of Variance (ANOVA) and Structural Equation Modelling Partial Least Square (SEM-PLS). The ANOVA results show that gender, age ratio, and residence (living area) are significant presumption factors. According to SEM-PLS model, the R-squared of non-ridership presumption variables toward the BRT execution as excellent public transportation is at 51.8% (moderate level). It is found that the economic variable affects the excellent public transportation variable is at 41.4%, and the social variable have a correlation with the excellent public transportation variable is at 36.2%, but not with the environment variable (5.6% only). Following up these findings, it is recommended that public engagement through the non-ridership presumption will lead the BRT provider to purpose some programs to improve the service and increase the occupancy. So that, the proposed program will attract the sense of awareness and public engagement of the non-ridership toward the BRT execution.

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High volume bus stop upstream average waiting time for working capacity and quality of service

Cited by 18 publications

References 10 publications

Time–space analysis to evaluate cell-based quality of service in bus rapid transit station platforms through passenger-specific area

Time–space analysis to evaluate cell-based quality of service in bus rapid transit station platforms through passenger-specific area

Capacity Estimation of On-Street, Mid-Block, Off-Line Bus Stops Considering Yield-to-Bus Rule

Non-Ridership Presumption Toward New Bus Rapid Transit Purwokerto-Purbalingga Execution

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