Bus Transit Operations Control: Review and an Experiment Involving Tri-Met's Automated Bus Dispatching System

Strathman, James G.; Kimpel, Thomas J.; Dueker, Kenneth J.; Gerhart, Richard L; Turner, K; Griffin, David; Callas, Steve

doi:10.5038/2375-0901.4.1.1

Cited by 48 publications

(36 citation statements)

References 15 publications

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“…The archived AVL/APC data have been used in various studies of operations control and service reliability (Strathman et al 1999;Strathman et al 2000;Strathman et al 2001a;Strathman et al 2001b), for route-level passenger demand modeling (Kimpel 2001), for models of trip and dwell time (Bertini and El-Geneidy 2004), and for evaluating schedule efficiency and operator performance (Strathman, et al 2002).…”

Section: Computer-aided Dispatch (Cad) Centermentioning

confidence: 99%

Determinants of Bus Dwell Time

Dueker¹,

Kimpel²,

Strathman³

et al. 2004

JPT

Self Cite

139

113

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Section: Computer-aided Dispatch (Cad) Centermentioning

confidence: 99%

Determinants of Bus Dwell Time

Dueker¹,

Kimpel²,

Strathman³

et al. 2004

JPT

Self Cite

139

113

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“…In normal service conditions, when perturbations do not result in service disruptions, vehicle holding (that is, to intentionally delay a vehicle at a stop after the alighting and boarding process of the passengers has ended) together with signal priority are the most important control methods (Desaulniers and Hickman 2007). Strathman et al (2001) examine the causes of unreliable service, provide a critical review of operation control practices, and discuss the application of automatic vehicle location (AVL) and automatic passenger counting (APC) technologies in control strategies, including vehicle holding.…”

Section: Literature Reviewmentioning

confidence: 99%

Transit vehicles’ headway distribution and service irregularity

Bellei

Gkoumas

2010

Public Transp

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Pairing, or bunching, of vehicles on a public transportation line influences\ud the adaptive choice at stops due to the random headways and waiting times it determines.\ud In order to ensure consistency with the characteristics of service perturbations,\ud as represented by a transit operation model, it is important to identify the headway\ud distributions representing service perturbations. A stochastic simulation model is developed\ud for a one-way transit line, which accounts for several service characteristics\ud (dwell time at stops, capacity constraint and arrivals during the dwell time). Samples\ud of headways at the main stops are utilized to build histograms of the headway’s frequencies\ud by their length, which allow to identify the functional forms and parameters\ud of the headway distributions. For these stops, density plots of consecutive headways\ud are also produced. Sensitivity analysis is carried out to identify the effect of key parameters\ud (dispatching headway, maximum load and running time)

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“…Also, dynamic holding was analysed in order to prevent bunching of vehicles. Finding the optimal holding strategy has been the focus of many studies, see a review of strategies in Strathman et al (2001). Cats et al (2012) test different holding strategies in terms of holding criteria and time point and find that headway-based strategies are superior to schedule-based strategies.…”

Section: Planning and Technology Scenariosmentioning

confidence: 99%

Analysing improvements to on-street public transport systems: a mesoscopic model approach

Ingvardson

Jensen

2017

Public Transp

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Light rail transit and bus rapid transit have shown to be efficient and costeffective in improving public transport systems of cities around the world. As these systems comprise various elements, which can be tailored to any given setting, e.g. pre-board fare-collection, holding strategies and other Advanced Public Transport Systems (APTS), the attractiveness of such systems depend heavily on their implementation. In the early planning stage it is advantageous to deploy simple and transparent models to evaluate possible ways of implementation. For this purpose, the present study develops a mesoscopic model which makes it possible to evaluate public transport operations in details, including dwell times, intelligent traffic signal timings and holding strategies while modelling impacts from other traffic using statistical distributional data thereby ensuring simplicity in use and fast computational times. This makes it appropriate for analysing the impacts of improvements to public transport operations, individually or in combination, in early planning stages. The paper presents a joint measure of reliability for such evaluations based on passengers' perceived travel time by considering headway time regularity and running time variability, i.e. taking into account waiting time and in-vehicle time. The approach was applied on a case study by assessing the effects of implementing segregated infrastructure and APTS-elements, individually and in combination. The results showed that the reliability of on-street public transport operations mainly depends on APTS-elements, and especially holding strategies, whereas pure infrastructure improvements induced travel time reductions. The results further suggested that synergy effects can be obtained by planning on-street public transport coherently in terms of reduced travel times and increased reliability.

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Bus Transit Operations Control: Review and an Experiment Involving Tri-Met's Automated Bus Dispatching System

Cited by 48 publications

References 15 publications

Determinants of Bus Dwell Time

Determinants of Bus Dwell Time

Transit vehicles’ headway distribution and service irregularity

Analysing improvements to on-street public transport systems: a mesoscopic model approach

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