Frequency-based transit assignment considering seat capacities

Schmöcker, Jan-Dirk; Fonzone, Achille; Shimamoto, Hiroshi; Kurauchi, Fumitaka; Bell, M.G.

doi:10.1016/j.trb.2010.07.002

Cited by 103 publications

(58 citation statements)

References 10 publications

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“…This has been recently incorporated into public transport assignment models such as Sumalee et al (2009), Leurent andLiu (2009), Hamdouch et al (2011) and Schmöcker et al (2011), who estimate the probability of getting a seat both when boarding a bus, and once on board if a passenger has to stand at the beginning of his/her trip. Passengers choose departure time and route according to their perceived travel disutility, which includes the probability of getting a seat (or failure to do so) as a key attribute.…”

Section: Effect On Route and Bus Choicementioning

confidence: 99%

Crowding in public transport systems: Effects on users, operation and implications for the estimation of demand

Tirachini

Hensher

Rose

2013

Transportation Research Part A: Policy and Practice

227

153

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The effects of high passenger density at bus stops, at rail stations, inside buses and trains are diverse. . This paper examines the multiple dimensions of passenger crowding related to public transport demand, supply and operations, including effects on operating speed, waiting time, travel time reliability, passengers' wellbeing, valuation of waiting and invehicle time savings, route and bus choice, and optimal levels of frequency, vehicle size and fare. Secondly, crowding externalities are estimated for rail and bus services in Sydney, in order to show the impact of crowding on the estimated value of in-vehicle time savings and demand prediction. Using Multinomial Logit (MNL) and Error Components models, we show that alternative assumptions concerning the threshold load factor that triggers a crowding externality effect do have an influence on the value of travel time (VTTS) for low occupancy levels (all passengers sitting); however, for high occupancy levels, alternative crowding models estimate similar VTTS. Importantly, if demand for a public transport service is estimated without explicit consideration of crowding as a source of disutility for passengers, demand will be overestimated if the service is designed to have a number of standees beyond a threshold, as analytically shown using a MNL choice model. 2

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Section: Effect On Route and Bus Choicementioning

confidence: 99%

Crowding in public transport systems: Effects on users, operation and implications for the estimation of demand

Tirachini

Hensher

Rose

2013

Transportation Research Part A: Policy and Practice

227

153

View full text Add to dashboard Cite

show abstract

“…The factor X means v/c is equal to the volume-to-capacity ratio, which is also applied to Equation (11). Furthermore, the equivalency factor ϕ(s b ) is 1.65 for a small bus (8 m), 2.19 for standard buses (12 m), 2.60 for rigid long buses (15 m), and 3.00 for articulated buses (18 m).…”

Section: Running Timementioning

confidence: 99%

“…The diagram of Figure 2 indicates that the FBS encountering an intersection experiences three processes, including deceleration, queuing time, and acceleration, which conform a queue type D/D/1.The first D denotes that the time between arrivals to the queue is deterministic type; the second D describes the deterministic service time distribution; lastly, the 1 indicates only one server at the station. Equation (11) can be derived to calculate the average uniform delay incurred every signal cycle by the FBS crossing one intersection. The formulation of Equation (11) is identical to what has been suggested as an analytical steady-state approach, like the Highway Capacity Manual (HCM) or the Canadian Capacity Guide for Signalized Intersections:…”

Section: Delay Timementioning

confidence: 99%

“…A "fail-to-sit" probability is introduced at boarding points with travel costs without relying on a firstcome-first-serve (FCFS) principle for many crowded buses in European countries [11]. A schedulebased equilibrium model is proposed assuming passengers use their own individual strategies [7].…”

Section: In-fbs Congested Costmentioning

confidence: 99%

“…The feelings of passengers are attributed to the estimation of the LOS of traveling time in the vehicle, i.e., the seat layout and bus size makes a significant contribution to passengers' utilities [11].…”

mentioning

confidence: 99%

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A Frequency-Based Assignment Model under Day-to-Day Information Evolution of Oversaturated Conditions on a Feeder Bus Service

2017

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Day-to-day information is increasingly being implemented in transit networks worldwide. Feeder bus service (FBS) plays a vital role in a public transit network by providing feeder access to hubs and rails. As a feeder service, a space-time path for frequent passengers is decided by its dynamic strategy procedure, in which a day-to-day information self-learning mechanism is identified and analyzed from our survey data. We formulate a frequency-based assignment model considering day-to-day evolution under oversaturated conditions, which takes into account the residual capacity of bus and the comfort feelings of sitting or standing. The core of our proposed model is to allocate the passengers on each segment belonging to their own paths according to multi-utilities transformed from the time values and parametric demands, such as frequency, bus capacity, seat comfort, and stop layout. The assignment method, albeit general, allows us to formulate an equivalent optimization problem in terms of interaction between the FBS' operation and frequent passengers' rational behaviors. Finally, a real application case is generated to test the ability of the modeling framework capturing the theoretical consequents, serving the passengers' dynamic externalities.

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Optimal design of a short‐turning strategy considering seat availability

Yang

2016

J of Advced Transportation

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Summary We develop a methodology to optimize the schedule coordination of a full‐stop service pattern and a short‐turning service pattern on a bus route. To capture the influence of bus crowding and seat availability on passengers' riding experience, we develop a Markov model to describe the seat‐searching process of a passenger and an approach to estimate the transition probabilities of the Markov model. An optimization model that incorporates the Markov model is proposed to design the short‐turning strategy. The proposed model minimizes the total cost, which includes operational cost, passengers' waiting time cost and passengers' in‐vehicle travel time cost. Algorithm is developed to produce optimal values of the decision variables. The proposed methodology is evaluated in a case study. Compared with methodologies that ignore the effect of bus crowding, the proposed methodology could better balance bus load along the route and between two service patterns, provide passengers with better riding experience and reduce the total cost. In addition, it is shown that the optimal design of the short‐turning strategy is sensitive to seat capacity. Copyright © 2016 John Wiley & Sons, Ltd.

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Frequency-based transit assignment considering seat capacities

Cited by 103 publications

References 10 publications

Crowding in public transport systems: Effects on users, operation and implications for the estimation of demand

Crowding in public transport systems: Effects on users, operation and implications for the estimation of demand

A Frequency-Based Assignment Model under Day-to-Day Information Evolution of Oversaturated Conditions on a Feeder Bus Service

Optimal design of a short‐turning strategy considering seat availability

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