Public Transport

Aims & Scope

The scope and purpose of the journal includes, but is not limited to, any type of research in the area of Public Transport: Planning and Operations.

As its core it serves the primary mission of advancing the state of the art and the state of the practice in computer-aided systems and scheduling in public transport.

The journal considers any type of subjects in this area especially with a focus to planning and scheduling, the common ground is the use of computer-aided methods and operations research techniques to improve information management, network and route planning, vehicle and crew scheduling and rostering, vehicle monitoring and management, and practical experience with scheduling and public transport planning methods.

Besides theoretical papers, the journal also publishes case studies and applications.

Public Transport addresses transport operators, consulting firms and academic institutions involved in development, utilization or research of computer-aided planning and scheduling in public transport.

View Aims & Scope

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Metrics & Ranking

Impact Factor

Year	Value
2025	2.2
2024	2.30

SJR (SCImago Journal Rank)

Year	Value
2024	0.749

Quartile

Year	Value
2024	Q1

h-index

Year	Value
2024	39

Journal Rank

Year	Value
2024	7413

Journal Citation Indicator

Year	Value
2024	271

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Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar
• Web of Science

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Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Computer Science, Decision Sciences, Engineering and Social Sciences, designed to support cutting-edge academic discovery.

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Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• An overview on vehicle scheduling models

  Citation: 199

  Authors: Stefan, Natalia

• The bus bridging problem in metro operations: conceptual framework, models and algorithms

  Citation: 129

  Authors: Konstantinos, Matthew G.

• Relationships between rail passengers’ satisfaction and service quality: a framework for identifying key service factors

  Citation: 125

  Authors: Laura, Gabriella

• Scheduling electric vehicles

  Citation: 104

  Authors: M. E., J. M., J. A.

• Trip purpose inference using automated fare collection data

  Citation: 98

  Authors: Sang Gu, Mark

• Predictive modelling of running and dwell times in railway traffic

  Citation: 97

  Authors: Pavle, Rob M. P.

• Metaheuristics for the transit route network design problem: a review and comparative analysis

  Citation: 95

  Authors: Christina, Konstantinos, Eleni

• Integrating line planning, timetabling, and vehicle scheduling: a customer-oriented heuristic

  Citation: 91

  Authors: Mathias, Anita

• Travel mode choice and transit route choice behavior in Montreal: insights from McGill University members commute patterns

  Citation: 89

  Authors: Naveen, Vincent, Ahmed M.

• Automated timetable design for demand-oriented service on suburban railways

  Citation: 82

  Authors: Thomas

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