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Public transport crowding valuation in a post-pandemic era

Yap, M.D. (author), Wong, Howard (author), Cats, O. (author)

It is important to understand how public transport passengers value on-board crowding since the outbreak of the COVID-19 pandemic. The main contribution of this study is to derive the crowding valuation of public transport passengers in a post-pandemic era entirely based on observed, actual passenger route choices. We derive passengers’...

journal article 2023

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Bus Network Design and Frequency Setting in the Post-COVID-19 Pandemic: The Case of London

Filgueiras, Manuel (author), Gkiotsalitis, Konstantinos (author), Yap, M.D. (author), Cats, O. (author), Lobo, António (author), Ferreira, Sara (author)

A transit network design frequency setting model is proposed to cope with the postpandemic passenger demand. The multiobjective transit network design and frequency setting problem (TNDFSP) seeks to find optimal routes and their associated frequencies to operate public transport services in an urban area. The objective is to redesign the...

journal article 2023

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A data driven approach to update public transport service elasticities

Wong, Howard (author), Yap, M.D. (author)

Understanding the passenger demand impacts of public transport service changes is a fundamental aspect of transport planning. The main objective of this study is to derive an updated Generalised Journey Time (GJT) elasticity for urban and metropolitan public transport networks, by applying a revealed preference approach using individual...

journal article 2023

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Beyond the dichotomy: How ride-hailing competes with and complements public transport

Cats, O. (author), Kucharski, R.M. (author), Danda, Santosh Rao (author), Yap, M.D. (author)

Since ride-hailing has become an important travel alternative in many cities worldwide, a fervent debate is underway on whether it competes with or complements public transport services. We use Uber trip data in six cities in the United States and Europe to identify the most attractive public transport alternative for each ride. We then...

journal article 2022

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Quantification and control of disruption propagation in multi-level public transport networks

Yap, M.D. (author), Cats, O. (author), Törnquist Krasemann, Johanna (author), van Oort, N. (author), Hoogendoorn, S.P. (author)

Due to the multi-level nature of public transport networks, disruption impacts may spill-over beyond the primary effects occurring at the disrupted network level. During a public transport disruption, it is therefore important to quantify and control the disruption impacts for the total public transport network, instead of delimiting the...

journal article 2022

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Analysis and prediction of ridership impacts during planned public transport disruptions

Yap, M.D. (author), Cats, O. (author)

Urban metro and tram networks are regularly subject to planned disruptions, including closures, resulting from the need to maintain and renew infrastructure. In this study, we first empirically analyse the passenger demand response to planned public transport disruptions based on individual passenger travel behaviour, based on which we infer...

journal article 2022

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Taking the path less travelled: Valuation of denied boarding in crowded public transport systems

Yap, M.D. (author), Cats, O. (author)

Many public transport networks worldwide experience high crowding levels. Overcrowding can result in passengers not able to board the first arriving vehicle. We infer how waiting time induced by being denied boarding in crowded public transport systems is valued by passengers, based on observed passenger route choice behaviour. For this purpose,...

journal article 2021

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Measuring, Predicting and Controlling Disruption Impacts for Urban Public Transport

Yap, M.D. (author)

Public transport systems can be subject to disruptions, which have negative impacts on passengers. Disruptions can result in additional in-vehicle time, waiting time, transfer time and extra transfers for passengers. In addition, perceived journey times might increase due to higher crowding levels on public transport services. Public transport...

doctoral thesis 2020

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Predicting disruptions and their passenger delay impacts for public transport stops

Yap, M.D. (author), Cats, O. (author)

Disruptions in public transport can have major implications for passengers and service providers. Our study objective is to develop a generic approach to predict how often different disruption types occur at different stations of a public transport network, and to predict the impact related to these disruptions as measured in terms of...

journal article 2020

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Analysis and Prediction of Disruptions in Metro Networks

Yap, M.D. (author), Cats, O. (author)

Public transport disruptions can result in major impacts for passengers and operator. Our study objective is to predict disruption exposure at different stations, incorporating their location-specific characteristics. Based on a 13-month incident database for the Washington metro network, we successfully develop a supervised learning model to...

conference paper 2019

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Where shall we sync? Clustering passenger flows to identify urban public transport hubs and their key synchronization priorities

Yap, M.D. (author), Luo, D. (author), Cats, O. (author), van Oort, N. (author), Hoogendoorn, S.P. (author)

Minimizing passenger transfer times through public transport (PT) transfer synchronization is important during tactical planning and real-time control. However, there are computational challenges for solving this Timetable Synchronization Problem (TSP) for large, real-world urban PT networks. Hence, in this study we propose a data-driven,...

journal article 2019

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Using passenger flows to determine key interchange connections for public transport synchronization

Yap, M.D. (author), Luo, D. (author), Cats, O. (author)

For large urban networks and hubs, optimizing transfer synchronization becomes computationally challenging. The objective of this paper is therefore to develop a generic, data-driven methodology to determine the key line/direction-combinations to synchronize based on passenger flows. We developed an approach to detect communities of directional...

conference paper 2018

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Controlling the propagation of passenger disruption impacts in multi-level public transport networks

Cats, O. (author), Yap, M.D. (author), van Oort, N. (author), Hoogendoorn, S.P. (author)

conference paper 2018

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Driver schedule efficiency vs. public transport robustness: A framework to quantify this trade-off based on passive data

Yap, M.D. (author), van Oort, N. (author)

More complex, efficient driver schedules reduce operator costs during undisrupted operations, but increase the disruption impact for passengers and operator once a disruption occurs. We develop an integrated framework to quantify the passenger and operator costs of disruptions explicitly as function of different driver schedule schemes. Since...

conference paper 2018

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Automatic bottleneck detection using AVL data: A case study in Amsterdam

Brands, T. (author), van Oort, N. (author), Yap, M.D. (author)

In daily practice, public transport authorities and operators are constantly searching for improvements in public transport operations. To this end, it is necessary to identify inefficiencies and bottlenecks in the current public transport services. In this paper, we propose a method to automatically detect bottlenecks in the public transport...

conference paper 2018

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Workshop 8 report: Big data in the digital age and how it can benefit public transport users

Yap, M.D. (author), Munizaga, Marcela (author)

This paper synthesizes evidence from Workshop 8 ‘Big data in the digital age and how it can benefit public transport users’ of the 15th International Conference on Competition and Ownership in Land Passenger Transport. Big data in public transportation has increasingly attracted the attention from both scientists and practitioners, resulting...

journal article 2018

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Improving predictions of public transport usage during disturbances based on smart card data

Yap, M.D. (author), Nijënstein, S. (author), van Oort, N. (author)

The availability of smart card data from public transport travelling the last decades allows analyzing current and predicting future public transport usage. Public transport models are commonly applied to predict ridership due to structural network changes, using a calibrated parameter set. Predicting the impact of planned disturbances, like...

journal article 2018

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Crowding valuation in urban tram and bus transportation based on smart card data

Yap, M.D. (author), Cats, O. (author), van Arem, B. (author)

Crowding in public transport can be of major influence on passengers’ travel experience and therefore affect route and mode choice. In this study, crowding valuation for urban tram and bus travelling is determined fully based on revealed preference data. Urban tram and bus crowding valuation is estimated in a European context based on a Dutch...

journal article 2018

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Identification and quantification of link vulnerability in multi-level public transport networks: a passenger perspective

Yap, M.D. (author), van Oort, N. (author), van Nes, R. (author), van Arem, B. (author)

Robust public transport networks are important, since disruptions decrease the public transport accessibility of areas. Despite this importance, the full passenger impacts of public transport network vulnerability have not yet been considered in science and practice. We have developed a methodology to identify the most vulnerable links in the...

journal article 2018

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Crowding Valuation in Urban Tram and Bus Transportation based on Smart Card Data

Yap, M.D. (author), Cats, O. (author), Yu, S (author), van Arem, B. (author)

Crowding in public transport can be of major influence on passengers’ travel experience and therefore affect route and mode choice. Therefore, it is important to understand how crowding in urban public transport is perceived by passengers. The availability of individual smart card transactions allows us to gain insights in revealed trade-offs...

conference paper 2017