Data driven improvements in public transport: The Dutch example

Due to reduced budgets, higher political expectations and increasing competition between operators, there is growing pressure on public transport companies and authorities to improve their operational efficiency. It is thus of utter importance for them to be able to identify inefficiencies, bottlenecks and potentials in their public transport...

Data-driven public transport ridership prediction approach including comfort aspects

The most important aspects on which passengers base their choice whether to travel by public transport are the perceived travel time, costs, reliability and comfort. Despite its importance, comfort is often not explicitly considered when predicting demand for public transport. In this paper, we include comfort level in a modelling framework by...

Data-driven public transport ridership prediction approach including comfort aspects

Betere OV prognoses met anonieme OV-Chipkaartdata

Door de introductie van de OV-Chipkaart komen er grote hoeveelheden data over reizigersstromen in het OV beschikbaar. Naast data over de voertuigprestaties (via GOVI bijv.) hebben de inzichten uit deze reizigersdata een enorm potentieel voor de optimalisatie van het OV-product. Dit artikel verkent de mogelijkheden om, de privacy van reizigers...

OV prognoses met anonieme OV-Chipkaartdata

Verkeersmodellen verrijken met onbetrouwbaarheid OV vanuit een reizigersperspectief

Incorporating unreliability of transit in transport demand models: Theoretical and practical approach

Nowadays, transport demand models do not explicitly evaluate the impacts of service reliability of transit. Service reliability of transit systems is adversely experienced by users, as it causes additional travel time and unsecure arrival times. Because of this, travelers are likely to perceive a higher utility from higher reliable transport...

Optimizing public transport planning and operations using automatic vehicle location data: The Dutch example

There is a growing pressure on urban public transport companies and authorities to improve efficiency, stemming from reduced budgets, political expectations and competition between operators. In order to find inefficiencies, bottlenecks and potentials in the public transport service, it is useful to learn from recorded operational data. We first...