Posts tagged revealed preference

Wat gaat MaaS ons brengen?

MaaS congres 2018: Niels van Oort is assistant professor public transport aan de TU Delft en doet onderzoek naar de effecten van nieuwe vervoerssytemen. Hij gaat de mogelijke impact van MaaS op reizigers en maatschappij toelichten, met voorbeelden van verschillende pilots en onderzoeken.

Zie HIER zijn bijdrage aan het MaaS congres 2018

The Potential of Demand Responsive Transport as a Complement to Public Transport

Demand Responsive Transport (DRT) offers a collective flexible travel alternative that can potentially complement Fixed Transit (FT). The combination of an on-demand and line-based services holds the promise of improved mobility and increased service coverage. However, insofar it remains unknown whether DRT services deliver such much anticipated improvements.

This study presents an assessment framework to evaluate the performance of DRT and related changes in accessibility and performs an empirical analysis for a recently introduced DRT service in the Netherlands. The framework includes a performance benchmark between DRT and FT based on the computation of generalized journey times of the DRT rides and the FT alternatives, and it can help identify whether DRT is used as complement or substitute of FT.
The framework covers the spatial and temporal dimensions, and the explicit consideration of rejected trips is an integral part of the evaluation. Results suggest large accessibility improvements for DRT users, especially for some underserved origin-destination pairs.

Read more of this work of Maria J. Alonso Gonzalez: TRB Paper and TRB Presentation

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

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 temporary track closures, on public transport ridership is however an unexplored area. In the Netherlands, this area becomes increasingly important, given the many track closures operators are confronted with the last and upcoming years. We investigated the passenger impact of four planned disturbances on the public transport network of Den Haag, the Netherlands, by comparing predicted and realized public transport ridership using smart card data. A two-step search procedure is applied to find a parameter set resulting in higher prediction accuracy. We found that in-vehicle time in rail-replacing bus services is perceived ≈1.1 times more negatively compared to in-vehicle time perception in the initial tram line. Besides, passengers do not seem to perceive the theoretical benefit of the usually higher frequency of rail-replacement bus services compared to the frequency of the replaced tram line. At last, no higher waiting time perception for temporary rail-replacement services could be found, compared to regular tram and bus services. The new parameter set leads to substantially higher prediction accuracy compared to the default parameter set. It supports public transport operators to better predict the required supply of rail-replacement services and to predict the impact on their revenues.

Read our TRB paper HERE

Find the poster HERE

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