Schedule-based transit assignment model with travel strategies and capacity constraints

Hamdouch, Younes; Lawphongpanich, Siriphong

doi:10.1016/j.trb.2007.11.005

Cited by 125 publications

(76 citation statements)

References 18 publications

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“…13 and Fig. 14), the inflow on queuing arcs (1, 21) and (1, 22) at Stop 1 and (2, 23) and (2,24) at Stop 2 stays constant during all the analysis period. …”

Section: Model Implementation and Numerical Examplesmentioning

confidence: 84%

“…A schedule-based approach has also been used [17,18,24] to represent the behaviour of passengers that choose a ranked set of runs (that make up an ordered set of "back-up travel plans") and know that, at each intermediate stop, they may not be able to board the best option, or that they may not be able to sit, because of capacity constraints. Thus, in this case the concept of hyperpath is applied to a different scenario: passengers know and trust the service timetable (this is one of the basic assumptions of schedule-based models) and can precisely select their best travel option; however, it is uncertain if they will be able to board/sit when congestion occurs.…”

Section: Background Research On Transit Congestionmentioning

confidence: 99%

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Dynamic user equilibrium in public transport networks with passenger congestion and hyperpaths

Trozzi

Gentile

Bell

et al. 2013

Transportation Research Part B: Methodological

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This is the accepted version of the paper.This version of the publication may differ from the final published version. Permanent repository link AbstractThis paper presents a Dynamic User Equilibrium for bus networks where recurrent overcrowding results in queues at stops. The route choice model embedded in the dynamic assignment explicitly considers common lines and strategies with alternative routes. As such, the shortest hyperpath problem is extended to a dynamic scenario with capacity constraints where the diversion probabilities depend on the time the stop is reached and on the expected congestion level at that time. In order to reproduce congestion for all the lines sharing a stop, the Bottleneck Queue model with time-varying exit capacity, introduced in Meschini et al. (2007), is extended. The above is applied to separate queues for each line in order to satisfy the First-In-First-Out principle within every attractive set, while allowing overtaking among passengers having different attractive sets but queuing single file.

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“…13 and Fig. 14), the inflow on queuing arcs (1, 21) and (1, 22) at Stop 1 and (2, 23) and (2,24) at Stop 2 stays constant during all the analysis period. …”

Section: Model Implementation and Numerical Examplesmentioning

confidence: 84%

Section: Background Research On Transit Congestionmentioning

confidence: 99%

Dynamic user equilibrium in public transport networks with passenger congestion and hyperpaths

Trozzi

Gentile

Bell

et al. 2013

Transportation Research Part B: Methodological

View full text Add to dashboard Cite

show abstract

“…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%

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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“…These model objectives are minimizing the total expected travel and waiting time [5][6][7] perceived total travel times [8], expected travel cost [9,10], general cost [11] (including; in-vehicle time, waiting time, walking time, a line change penalty), total vehicle operation cost [12], optimize transit lines timetables with fleet size and vehicle services [13], utility maximization [14]. Transit assignment models are solved with the gradient projection method, minimum cost hyperpath search algorithm, method of successive averages algorithm, iterated local search algorithm and Newton method.…”

Section: Transit Assignmentmentioning

confidence: 99%

Considering sustainability in the planning of transit systems: Istanbul case

Buran¹,

Feyzıog̃lu

2013

WIT Transactions on the Built Environment

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Traditionally, minimization of the total travel time spent by the passenger in the system is the most preferred objective while planning transit systems. To satisfy this objective, forecasted travel demands between zones and characteristics of the available fleet are taken into account, and at the end of the planning process, optimum frequencies of each transit lines are identified. Unfortunately, this planning approach is not sufficient as the negative effects of the global warming are growing each day. Fossil fuels are the primary energy sources for transport systems and accordingly, the emission of the greenhouse gases especially carbon dioxide is accredited to this industry. Hence, it is impossible to ignore environmental requirements in the transit planning phase. In this study, we developed a bi-level and bi-objective optimization model to identify the optimum line frequencies. One of the objectives is to minimize the mean travel time of the passengers. The other objective is to minimize the total emission. A genetic algorithm is developed to solve this mathematical programming problem. A large instance related to Istanbul transit system involving 39 zones and 463 bus lines is solved with this solution method and results are elaborated.

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Schedule-based transit assignment model with travel strategies and capacity constraints

Cited by 125 publications

References 18 publications

Dynamic user equilibrium in public transport networks with passenger congestion and hyperpaths

Dynamic user equilibrium in public transport networks with passenger congestion and hyperpaths

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

Considering sustainability in the planning of transit systems: Istanbul case

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