Deduction of Passengers' Route Choices From Smart Card Data

Hurk, Evelien van der; Kroon, Leo; Maróti, Gábor; Vervest, Peter

doi:10.1109/tits.2014.2333583

Cited by 59 publications

(28 citation statements)

References 14 publications

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“…For instance, delay information can be obtained from recognition or positioning sensors on-board vehicles and at stops [5], information about the travelers' actual destinations (used to provide efficient transport alternatives) can be collected from smart card tickets [30], and micro-navigation information can be attained using IoT-based recognition systems that are located on-board vehicles and across stations [31]. In some situations, data similar to those collected already exist in other types of systems.…”

Section: Travellingmentioning

confidence: 99%

The Fourth Wave of Digitalization and Public Transport: Opportunities and Challenges

et al. 2016

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Abstract:We investigate the opportunities and challenges of the forth wave of digitalization, also referred to as the Internet of Things (IoT), with respect to public transport and how it can support sustainable development of society. Environmental, economical, and social perspectives are considered through analysis of the existing literature and explorative studies. We conclude that there are great opportunities for both transport operators and planners, as well as for the travelers. We describe and analyze a number of concrete opportunities for each of these actors. However, in order to realize these opportunities, there are also a number of challenges that needs to be addressed. There are both technical challenges, such as data collection issues, interoperability, scalability and information security, and non-technical challenges such as business models, usability, privacy issues, and deployment.

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Section: Travellingmentioning

confidence: 99%

The Fourth Wave of Digitalization and Public Transport: Opportunities and Challenges

et al. 2016

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“…Oyster card in London and Access card in Stockholm). The smart card detection may occur at PTS entrance and exit (Lathia and Capra 2011;Zhao et al 2017;van der Hurk et al 2014), at vehicle entrance or on platform, waiting to board a certain vehicle (Wang et al 2011;Munizaga and Palma 2012;Ma et al 2013;Arnone et al 2016), at vehicle entrance and exit (Ma et al 2013;van Oort et al 2015;Arnone et al 2016), or when onboard via a contactless smart card (Zeller 2013) (cf. Table 2).…”

Section: Review Summarymentioning

confidence: 99%

Exploring the potential of using real-time traveler data in public transport disturbance management

Jevinger

Persson

2019

Public Transp

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New and emerging technologies, such as connected sensors, smartphones and smart cards, offer new possibilities to collect rich real-time information about travelers. Moreover, smartphones also enable travelers to actively share information, for instance, about their intended travel plans. This type of information can be used to improve public transport disturbance management. In this paper, the potential gain of collecting different types of information about travelers is explored to support action decisions made by public transport actors, during unplanned disturbances. Based on interviews and workshops, the paper provides a mapping between different information types and possible action decisions that can be supported. Furthermore, based on a literature review focused on current and potential technical solutions, a guidance to which solutions support which type of action decisions, is also provided. Amongst others, the results show that automated fare collection, which is one of the most commonly implemented systems providing real-time information about the traveler, can support a large number of action decisions relevant in unplanned disturbance scenarios. The technical solution providing the most extensive information, and thereby providing the best support for the action decisions, involves smartphone apps delivering user-generated information. The drawback with this solution is that it might violate privacy, and that it typically relies on the travelers providing relevant information voluntarily.

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“…Further exploration of customer behavior includes van der Hurk et al [33] which presents a methodology for extracting passenger routes based on smart card data from the Netherlands Rail System. This work demonstrates how passenger service, based on passenger route choice, can be analyzed based on the route detection mechanism.…”

Section: A Use Of Transportmentioning

confidence: 99%

Visual Analytics of Mobility and Transportation: State of the Art and Further Research Directions

Andrienko

Chen

Maciejewski

et al. 2017

IEEE Trans. Intell. Transport. Syst.

123

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This is the accepted version of the paper.This version of the publication may differ from the final published version. City Research Online  Abstract-Many cities and countries are now striving to create intelligent transportation systems that utilize the current abundance of multisource and multiform data related to the functionality and use of transportation infrastructure to better support human mobility, interests, and lifestyles. Such intelligent transportation systems aim to provide novel services that can enable transportation consumers and managers to be better informed and make safer and more efficient use of the infrastructure. However, the transportation domain is characterized by both complex data and complex problems, which calls for visual analytics approaches. The science of visual analytics is continuing to develop principles, methods, and tools to enable synergistic work between humans and computers through interactive visual interfaces. Such interfaces support the unique capabilities of humans (such as the flexible application of prior knowledge and experiences, creative thinking, and insight) and couple these abilities with machines' computational strengths, enabling the generation of new knowledge from large and complex data. In this paper, we describe recent developments in visual analytics that are related to the study of movement and transportation systems and discuss how visual analytics can enable and improve the intelligent transportation systems of the future. We provide a survey of literature from the visual analytics domain and organize the survey with respect to different types of transportation data, movement and its relationship to infrastructure and behavior, and modeling and planning. We conclude with lessons learned and future directions including social transportation, recommender systems, and policy implications. Permanent repository link

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Deduction of Passengers' Route Choices From Smart Card Data

Cited by 59 publications

References 14 publications

The Fourth Wave of Digitalization and Public Transport: Opportunities and Challenges

The Fourth Wave of Digitalization and Public Transport: Opportunities and Challenges

Exploring the potential of using real-time traveler data in public transport disturbance management

Visual Analytics of Mobility and Transportation: State of the Art and Further Research Directions

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