The impact of irregular headways on seat availability

Babaei, Mohsen; Schmöcker, Jan-Dirk; Mohaymany, Afshin Shariat

doi:10.1080/23249935.2013.795198

Cited by 14 publications

(8 citation statements)

References 29 publications

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“…While these advancements contribute to the consideration of reliability in the TAM domain, none of the abovementioned studies captures the dynamic congestion effects of the interaction between service uncertainty and passenger flows. Service reliability propagates dynamically in transit systems with the bunching phenomenon being the most noticeable phenomenon (Cats et al 2011), where congestion reinforces this process (Babaei et al 2014).…”

Section: Literature Reviewmentioning

confidence: 99%

“…Previous studies calculated the probability of failing to get a seat based on the combination of rules (a) and (b) in frequency-based (Schmöcker et al 2011) and schedule-based (Hamdouch et al 2011) transit assignment models. The relation between service regularity and seat availability was formulated analytically by Babaei et al (2014). In contrast, the seating priority rules are applied explicitly in BusMezzo based on the interaction between individual passengers and vehicle trips.…”

Section: Impacts Of Congestion On On-board Discomfortmentioning

confidence: 99%

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A dynamic stochastic model for evaluating congestion and crowding effects in transit systems

Cats

West

Eliasson

2016

Transportation Research Part B: Methodological

106

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One of the most common motivations for public transport investments is to reduce congestion and increase capacity. Public transport congestion leads to crowding discomfort, denied boardings and lower service reliability. However, transit assignment models and appraisal methodologies usually do not account for the dynamics of public transport congestion and crowding and thus potentially underestimate the related benefits. This study develops a method to capture the benefits of increased capacity by using a dynamic and stochastic transit assignment model. Using an agent-based public transport simulation model, we dynamically model the evolution of network reliability and on-board crowding. The model is embedded in a comprehensive framework for project appraisal. A case study of a metro extension that partially replaces an overloaded bus network in Stockholm demonstrates that congestion effects may account for a substantial share of the expected benefits. A cost-benefit analysis based on a conventional static model will miss more than a third of the benefits. This suggests that failure to represent dynamic congestion effects may substantially underestimate the benefits of projects, especially if they are primarily intended to increase capacity rather than to reduce travel times.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Impacts Of Congestion On On-board Discomfortmentioning

confidence: 99%

A dynamic stochastic model for evaluating congestion and crowding effects in transit systems

Cats

West

Eliasson

2016

Transportation Research Part B: Methodological

106

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“…The Babaei et al (2014) had shown that headway can significantly affect seat availability, and seat reliability becomes high with low service frequency. However, if a bus company blindly increases headway to improve seat availability, it will not only make its costs uncontrollable; but will also easily lead to bunching effects.…”

Section: Model Formulationmentioning

confidence: 99%

A Mass Transit Equilibrium Problem with Bottleneck Congestion and Capacity Constraints

Shang

Tian

Chu

et al. 2023

Preprint

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Seat capacity setting greatly affects vehicle capacity. Increasing the number of seats allows more passengers to benefit from comfortable travel conditions but reduces the available space for standing passengers and the total capacity of the vehicle. By reducing the number of seats, the operator increases the capacity of the vehicle but most passengers do not find an available seat. Without changing the size of the bus, the operator chooses the desirable seat capacity when purchasing the bus, which can maximize vehicle capacity and allow passengers to have more opportunities to get a seat. Considering capacity constraints, this paper establishes multiple origins and a single destination equilibrium model to study the travel behaviors during peak-period. A bi-level programming model is considered to meet the equilibrium cost. The result shows that we succeed in finding an optimal seat capacity to make the total travel cost be lowest.

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“…However, service reliability propagates dynamically in transit systems with the bunching phenomenon being the most noticeable phenomenon . Moreover, congestion reinforces this process .…”

Section: Congestion In Transit Assignment Models: a Reviewmentioning

confidence: 99%

Modelling public transport on‐board congestion: comparing schedule‐based and agent‐based assignment approaches and their implications

Cats

Hartl

2016

J of Advced Transportation

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Summary Transit systems are subject to congestion that influences system performance and level of service. The evaluation of measures to relieve congestion requires models that can capture their network effects and passengers' adaptation. In particular, on‐board congestion leads to an increase of crowding discomfort and denied boarding and a decrease in service reliability. This study performs a systematic comparison of alternative approaches to modelling on‐board congestion in transit networks. In particular, the congestion‐related functionalities of a schedule‐based model and an agent‐based transit assignment model are investigated, by comparing VISUM and BusMezzo, respectively. The theoretical background, modelling principles and implementation details of the alternative models are examined and demonstrated by testing various operational scenarios for an example network. The results suggest that differences in modelling passenger arrival process, choice‐set generation and route choice model yield systematically different passenger loads. The schedule‐based model is insensitive to a uniform increase in demand or decrease in capacity when caused by either vehicle capacity or service frequency reduction. In contrast, nominal travel times increase in the agent‐based model as demand increases or capacity decreases. The marginal increase in travel time increases as the network becomes more saturated. Whilst none of the existing models capture the full range of congestion effects and related behavioural responses, existing models can support different planning decisions. Copyright © 2016 John Wiley & Sons, Ltd.

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The impact of irregular headways on seat availability

Cited by 14 publications

References 29 publications

A dynamic stochastic model for evaluating congestion and crowding effects in transit systems

A dynamic stochastic model for evaluating congestion and crowding effects in transit systems

A Mass Transit Equilibrium Problem with Bottleneck Congestion and Capacity Constraints

Modelling public transport on‐board congestion: comparing schedule‐based and agent‐based assignment approaches and their implications

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