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

Jonathan M. Bunker ()
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Jonathan M. Bunker: Queensland University of Technology

Public Transport, 2018, vol. 10, issue 2, No 6, 333 pages

Abstract: Abstract High volume bus facilities range from on-street facilities to dedicated Bus Rapid Transit (BRT) facilities. The aim of this study is to better understand performance by directly relating critical stop bus capacity to quality of service (QOS), which measures performance from the passengers’ and operator’s perspectives. The US transit capacity and quality of service manual methodology estimates facility bus capacity based on critical stop operation using a failure rate approach. However, this approach is inaccurate under high volume conditions and the failure rate is a difficult measure to prescribe and to interpret. This research provides an improved understanding of operation by instead considering bus upstream average waiting time to measure capacity and QOS performance, because it is experienced directly by passengers and is an indicator of the impact upon general traffic. A fundamental microscopic simulation model is developed with many bus stop operational aspects occurring stochastically, including upstream arrivals. An empirical upstream average waiting time model is calibrated for five bus stop scenarios including BRT and on-street conditions. This is then used to determine working capacity based on QOS threshold upstream average waiting time. Assigning a worse threshold gives diminishing returns in working capacity, particularly for waiting times beyond 60 s. For an assigned threshold, as loading area processing time reduces, working capacity increases more markedly. This demonstrates that BRT stations are more productive than general on-street bus stops. An example shows that a policy decision exists for the operator as to which QOS threshold to accept in balance with working capacity that suits the desired schedule. It is also discussed that the model enables the operator to evaluate the impact of design or operational changes as well as timetable changes on capacity and QOS.

Keywords: Transit capacity; Transit quality of service; Bus; Passenger; Delay (search for similar items in EconPapers)
JEL-codes: R41 (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (6)

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DOI: 10.1007/s12469-018-0179-1

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