Posts in category Papers

Urban Demand Responsive Transport in the Mobility as a Service ecosystem: its role and potential market share

Mobility as a Service (MaaS) is entering the transportation market. MaaS aims at the full
integration of the existing transportation services and it offers tailored mobility packages to
the user. In MaaS ecosystems, on-demand services play an important role as complement to
public transport due to their flexibility. However, to date, most attention has been placed on
individual on-demand services. This study focuses on Demand Responsive Transport (DRT):
collective on-demand services. Using an on-line survey, we analysed the characteristics of
the respondents who chose different modes of transport among their selected modes.
Results find a distinctive pattern in the willingness of users to use different modes, with
different levels in what could be considered as a multimodality ladder. The different rungs of
it would be: 1st car (if available), 2nd public transport, 3rd DRT and 4th taxi-like services.
This way, a person standing on the third rung would include car, public transport and DRT in
their consideration set, but not taxi. This finding suggests that, if implemented in the right
way, DRT services can attract a larger number of users than taxi-like services, especially in a
MaaS ecosystem where initial barriers to try this service can be lessened.

Find the paper presented by Maria Alonso Gonzalez at the Thredbo conference in Stockholm HERE

The wider benefits of high quality public transport for cities

The true value of public transport is often underestimated systematically while assessing transit impacts of proposed projects. During the planning and assessment of new or improved connections, infrastructure or services, often only the costs of operations, construction and the revenues with regard to fares and travel time savings are accounted for. This approach provides insights into the performance of public transport to some extent, but disregards many other (positive) effects the provision of public services has. Many of which impose an advantage over competing modes of transport. This could result in the postponement or even cancellation of plans, as means are scarce and invested where gains are directly visible. Thus, to enable a fairer assessment of public transport plans, more insight is required into the wider benefits of its operations and impacts on passengers and the environment.

To gain these insights, we developed a methodology to quantify the value of public transport using the five E’s: Effective mobility, Efficient city, Economy, Environment and Equity. Together these aspects provide a better indication of all potential benefits of public transport.

Read more in this ETC 2017 conference paper.

Understanding the trip and user characteristics of the combined bicycle and transit mode

Several cities around the world are facing mobility related problems such as traffic congestion and air pollution. Although limited individually, the combination of bicycle and transit offers speed and accessibility; by complementing each other’s characteristics the bicycle and transit combination can compete with automobiles. Recognising this, several studies have investigated policies that encourage integration of these modes. However, empirical analysis of the actual users and trips of the combined mode is largely missing. This study addresses this gap by (i) reviewing empirical findings on related modes, (ii) deriving user and trip characteristics of the bicycle and transit mode in the Netherlands, and (iii) applying latent class cluster analysis to discover prototypical users based on their socio-demographic attributes. Most trips by this mode are found to be for relatively long commutes where transit is in the form of trains, and bicycle and walking are access and egress modes respectively. Furthermore, seven user groups are identified and their spatial and temporal travel behaviour is discussed. Transport authorities may use the empirical results in this study to further streamline integration of bicycle and transit for its largest users as well as to tailor policies to attract more travellers.

Find our Thredbo conference presentation HERE

Read our paper HERE

Modelling Multimodal Transit Networks: Integration of bus networks with walking and cycling

Demand for (public) transportation is subject to dynamics affected by technological, spatial, societal and demographic aspects. The political environment, together with financial and spatial constraints limit the possibilities to address transit issues arising from growing demand through the construction of new infrastructure. Upgrading of existing services and improving integration over the entire trip chain (including cycling) are two options that can address these transport issues. However, transport planners and transport service operators often fail to include the entire trip when improving services, as improvement is normally achieved through the adaptations of characteristics (e.g. speeds, stop distances) of the services.
Our developed framework consists of two parts: one to assess the characteristics of the different bus services and their access and egress modes, and one to assess the effects of integration of these services, which includes the modelling and analysis in a regional transit model. The framework has successfully been applied to a case study showing that bus systems with higher frequencies and speeds can attract twice the amount of cyclists on the access and egress sides. It also shows that passengers accept longer access and egress distances with more positive characteristics of the bus service (higher speeds, higher frequencies).

Find the presentation of Judith Brand at MT-ITS in Napoli HERE

Find our paper HERE

Insights into door-to-door travel patterns of public transport passengers

Public transport enables fast and reliable station to station journeys. To assess passenger travel patterns and to infer actual quality of service, smartcard and AVL data offer great opportunities. There is, however, an increasing interest in insights into access and egress dynamics of public transport riders as well. What is the size of a stop’s catchment area, which modes are used, and how long and reliable are access and egress times? The answers to these and other questions enable optimization of the total mobility system, thereby also increasing public transport ridership and efficiency. Sufficient biking access of public transport stops (routes and parking), for instance, offer opportunities to increase public transport stopping distances, thereby increasing operational speed and reliability, without compromising accessibility of service areas. We developed a methodology to calculate and demonstrate these dynamics by using new and existing data technologies, namely AVL, survey and new promising app.

Find the Transit Data Conference abstract HERE and our presentation HERE

Special Issue Stedelijk OV Tijdschrift Vervoerwetenschap

Onze steden worden steeds belangrijker. Tegen 2050 woont ca. 70% van de totale wereldbevolking in ‘de’ stad. Het wordt een grote uitdaging voor ons allen om die steden leefbaar en economisch vitaal te houden. Openbaar vervoer (OV) speelt een essentiële rol bij deze uitdaging. Goede bereikbaarheid van de economische en sociale kerngebieden is een absolute voorwaarde voor het succes van een stad en OV is daarbij een onmisbare schakel. In dit special issue “Stedelijk OV” presenteren wij u een verzameling wetenschappelijke artikelen die helpt om het OV en daarmee de stad tot een succes te (blijven) maken. Stuk voor stuk wetenschappelijk onderzoek – direct toepasbaar voor een praktisch vervolg in beleid, planning en/of uitvoering.

Lees meer: Voorwoord special issue

Optimization of a passenger railway transportation plan considering mobility flows and service quality

This research focuses on designing transportation plan for SNCF Transilien (French railway
operator for the Parisian suburban mass transit). The objective is to develop methods
and decision support tools to propose a timetable adapted to the passenger demand in the
Parisian mass transit system, including comfort and reliability criterias.
This paper aims to present the first step of this research. We propose a graph theoretic
ILP formulation for the Line Planning Problem, minimizing both travelers travel time and
operating cost. We furthermore develop a multi-objective method to solve this problem.
This method offers a pool of solutions in order to let the final designer choose the solution.
We report computational results on real world instances provided from SNCF Transilien.

Check the RAIL Lille paper of Lucile Brethome et al. HERE

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

Investigating potential transit ridership by fusing smartcard and GSM data

The public transport industry faces challenges to cater for the variety of mobility patterns and corresponding needs and preferences of passengers. Travel habit surveys provide information on the overall travel demand as well as its spatial variation. However, it often does not include information on temporal variations. By means of data fusion of smartcard and Global System for Mobile Communications (GSM) data, spatial and temporal patterns of public transport usage versus the overall travel demand are examined. The analysis is performed by contrasting different spatial and temporal levels of smartcard and GSM data. The methodology is applied to a case study in Rotterdam, the Netherlands, to analyze whether the current service span is adequate. The results suggest that there is potential demand for 10 extending public transport service span on both ends. In the early mornings, right before transit operations are resumed, an hour-on-hour increase in visitor occupancy of 33-88% is observed in several zones, thereby showing potential demand for additional public transport services. The proposed data fusion method showed to be valuable in supporting tactical transit planning and decision making and can easily be applied to other origin-destination transport data.

Read our TRB paper HERE

Find our presentation HERE

Het verbeteren van de last-mile in een OV reis met automatische voertuigen

De last-mile in een openbaar vervoer (OV) reis is een van de meest hinderlijke gedeelten van een reis per OV. Hierdoor is het OV veelal niet in staat om te kunnen concurreren met de auto. De oorzaak kan deels worden gevonden in het gebrek aan flexibiliteit en de lage snelheden die de veelal conventionele vervoersmiddelen op de last-mile kenmerken. Recente technologische ontwikkelingen maken innovatieve vraaggestuurde vervoersconcepten met zelfrijdende voertuigen mogelijk. Deze zijn onafhankelijk van vaste infrastructuur en zouden ideaal op de last-mile ingezet kunnen worden, om zo het diffuse patroon en lage vervoersvolume efficiënt te bedienen.

Om de vervoerwaarde en de prestatie van een vraaggestuurd vervoersysteem met zelfrijdende voertuigen op de last-mile te bepalen is als case: Station Delft-Zuid – TU Delft gekozen. Bij een vervoerwaarde studie met dergelijke innovatieve techniek wordt verwacht dat psychologische factoren, naast de puur instrumentele aspecten, expliciet een rol spelen in de vervoerwijzekeuze van reizigers. Het meenemen van deze preferenties is daarom van belang, teneinde de vervoerwaarde niet substantieel te over- of onderschatten. In dit paper zijn de uitkomsten van twee onderzoeken gecombineerd, een instrumenteel onderzoek (simulatiemodel + enquête) naar de vervoerwaarde van een systeem van zelfrijdende voertuigen en een stated preference (SP)-experiment om de invloed van diverse psychologische factoren op de vervoerwaarde te bepalen.
De resultaten laten zien dat er een aanzienlijke vervoerwaarde bestaat voor zelfrijdende voertuigen op de last-mile, te weten 57% van de steekproefpopulatie. Met het simulatiemodel zijn diverse ITS maatregelen gesimuleerd, deze maatregelen omvatten wijzigingen in de netwerkstructuur, voertuiggedrag en het reizigersgedrag.
De prestatie van het last-mile systeem, bleek veelal positief beïnvloedt te worden door bovenstaande maatregelen. Effecten werden gemeten in een vergroting van de systeemcapaciteit, een reductie van de gemiddelde wachttijd ofwel van de gemiddelde reistijd. Het parallel toepassen van deze maatregelen realiseert een aantrekkelijkere concurrentiepositie ten opzichte van de conventionele vervoerswijzen. De meest kenmerkende maatregel, het strategisch plaatsen van voertuigen, op locaties voorafgaand aan het ontstaan van vervoersvraag laat een reductie in de gemiddelde wachttijd van 40% zien.
Uit het SP-experiment blijkt dat de attitudes ‘duurzaamheid’ en ‘vertrouwen’ de twee belangrijkste aspecten zijn in de vervoerwijzekeuze, terwijl de in-voertuigtijd niet minder negatief wordt ervaren dan in een door de reiziger gereden carsharing systeem. Dit suggereert dat de gebruikelijk genoemde voordelen van zelfrijdende voertuigen wellicht nog niet worden ervaren door de reiziger van vandaag, en illustreert het belang om hier aandacht aan te schenken voor een succesvolle implementatie van zelfrijdende voertuigen.

Lees het CVS paper HIER

Zie de CVS presentatie HIER

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