A self-coördinating bus route to resist bus bunching

Bartholdi, John J.; Eisenstein, Donald D.

doi:10.1016/j.trb.2011.11.001

Cited by 210 publications

(138 citation statements)

References 10 publications

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“…Then, variables h ks should be in seconds or in minutes and therefore integer variables. Preliminary results showed no drastic increment in the computing times when bus holding variables h ks are integer [1,4,6,15].…”

Section: Methodology and Approachmentioning

confidence: 95%

“…In Daganzo and Pilachowski [5] the authors continuously adjust bus cruising speed based on a cooperative two-way-based approach that considers the headways of the previous and later buses. Bartholdi III and Eisenstein [1] abandon the idea of any a priori target headway, allowing headways to dynamically self-equalize by implementing a simple holding rule at a control point. It is worth noting that the aim of the previously mentioned studies is to maintain headways equally, so they do not consider timetables where the headways may be different for each pair of buses and they are not apt for situations when the buses reach their capacities.…”

Section: State Of the Art Research In Real-time Bus Operationsmentioning

confidence: 99%

See 1 more Smart Citation

Linear Bus Holding Model for Real-Time Traffic Network Control

Hernández-Landa

Morales-Marroquín

Nigenda

et al. 2015

Applied Simulation and Optimization

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One of the most annoying problems in urban bus operations is bus bunching, which happens when two or more buses arrive at a stop nose to tail. Bus bunching reflects an unreliable service that affects transit operations by increasing passenger-waiting times. This work proposes a linear mathematical programming model that establishes bus holding times at certain stops along a transit corridor to avoid bus bunching. Our approach needs real-time input, so we simulate a transit corridor and apply our mathematical model to the data generated. Thus, the inherent variability of a transit system is considered by the simulation, while the optimization model takes into account the key variables and constraints of the bus operation. Our methodology reduces overall passenger-waiting times efficiently given our linear programming model, with the characteristic of applying control intervals just every 5 min.

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Section: Methodology and Approachmentioning

confidence: 95%

Section: State Of the Art Research In Real-time Bus Operationsmentioning

confidence: 99%

Linear Bus Holding Model for Real-Time Traffic Network Control

Hernández-Landa

Morales-Marroquín

Nigenda

et al. 2015

Applied Simulation and Optimization

View full text Add to dashboard Cite

show abstract

“…However, Bartholdi and Eisenstein aim to find the most suitable headways for the current situation. The strategy can make the system optimal rather than uniform headway [19]. As the vehicles' seating capacity is limited, as is the tolerance of passengers, most of the studied holding strategies are difficult to apply in practice.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The holding strategy only [19] and stop-skipping only [27] are carried out and the results are compared to the proposed hybrid strategy. The combination of the weighting factors is set as θ 1 : θ 2 : θ 3 " 6 : 3 : 1.…”

Section: Performance Evaluation Compared To Other Strategymentioning

confidence: 99%

Real-Time Hybrid In-Station Bus Dispatching Strategy Based on Mixed Integer Programming

Zhang

2016

Information

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Abstract:The actual bus headway often deviates from the planned departure frequency because of external factors, such as traffic conditions and public transport demand, leading to transit resource waste and reducing the quality of service. In view of the existing shortcomings of the current dispatching strategy, a mixed integer programming model, integrating a bus-holding and stop-skipping strategy, is constructed to improve transit service with a minimum cost. The real-time optimal holding and stop-skipping strategies can be obtained by solving the proposed model using the Lagrangian relaxation algorithm. A numerical example is conducted using real transit GPS (Global Position System) and IC (Intelligent Card) data in Harbin. The results show that compared to a single control strategy, the proposed hybrid model is a better trade-off between the quality of the transit service and the operation cost. Notably, such a strategy would produce a minimal passengers' average travel time coefficient. It is a great help for promoting the transit service level and increasing competitiveness.

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“…The typical objective of a bus holding strategy is to ensure that the waiting times of passengers at stops do not vary significantly from the planned ones. However, recent works, such as the work of Bartholdi and Eisenstein [10], focused on maintaining even headways between bus trips at the locations of the control point stops without adhering to the planned headway values. Although bus holding can be proved beneficial to bus operations, several works have proposed to introduce limitations on holding strategies because extensive holding of bus trips can cause inconvenience to passengers, overcrowding at stops and "schedule sliding" if the bus trips are postponed due to holding (Delgado et al [11]).…”

Section: Introductionmentioning

confidence: 99%

Bus Operations Scheduling Subject to Resource Constraints Using Evolutionary Optimization

Gkiotsalitis¹,

Kumar²

2018

Informatics

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Abstract:In public transport operations, vehicles tend to bunch together due to the instability of passenger demand and traffic conditions. Fluctuation of the expected waiting times of passengers at bus stops due to bus bunching is perceived as service unreliability and degrades the overall quality of service. For assessing the performance of high-frequency bus services, transportation authorities monitor the daily operations via Transit Management Systems (TMS) that collect vehicle positioning information in near real-time. This work explores the potential of using Automated Vehicle Location (AVL) data from the running vehicles for generating bus schedules that improve the service reliability and conform to various regulatory constraints. The computer-aided generation of optimal bus schedules is a tedious task due to the nonlinear and multi-variable nature of the bus scheduling problem. For this reason, this work develops a two-level approach where (i) the regulatory constraints are satisfied and (ii) the waiting times of passengers are optimized with the introduction of an evolutionary algorithm. This work also discusses the experimental results from the implementation of such an approach in a bi-directional bus line operated by a major bus operator in northern Europe.

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A self-coördinating bus route to resist bus bunching

Cited by 210 publications

References 10 publications

Linear Bus Holding Model for Real-Time Traffic Network Control

Linear Bus Holding Model for Real-Time Traffic Network Control

Real-Time Hybrid In-Station Bus Dispatching Strategy Based on Mixed Integer Programming

Bus Operations Scheduling Subject to Resource Constraints Using Evolutionary Optimization

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