Posts in category English
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 incorporating capacity in the public transport assignment. This modelling framework is applied in the public transport model of HTM, the urban public transport operator of The Hague. The current transportation demand is directly derived from smart card data and future demand is estimated using an elasticity based approach. The case study results indicate that not considering capacity and comfort effects can lead to a substantial underestimation of effects of certain measures aiming to improve public transport (up to 30%). We also illustrate that this extended modelling framework can be applied in practice: it has a short computation time and leads to better predictions of public transport demand.
Check our presentation: Presentation CASPT2015
Read our full paper: Van Oort et al: Datadriven PT modelling CASPT2015
Transport Thursday: Investing in cities
In recent years, state-of-the-art public transport, including light rail, has seen strong worldwide growth. Increasing numbers of different types are emerging, both on the drawing board and on the streets. What lessons can we learn from all of these ideas and projects? Rob van der Bijl, Bert Bukman and Niels van Oort conducted research into 47 light-rail projects in the Netherlands and elsewhere and wrote a book on this entitled, ‘Investeren in de stad. Lessen uit 47 light rail projecten ‘ (‘Investing in the city. Lessons from 47 light-rail projects’). On this special Transport Thursday, they will be sharing their most important lessons and experiences (from decision-making through to operation) in achieving successful state-of-the-art public transport, a key driver in our new smart cities.
Check our presetation: Transport Thursday Van Oort 2015
Opportunities and challenges for automated vehicles (individual, public and freight transport)
Since several years many developments regarding self-driving, automated vehicles (AVs) take place. Within the coming years it is expected that automated vehicles are becoming part of our transportation system. Therefore it’s becoming more and more important for policy makers to get insights into the state-of-the-art developments around AVs, in order to foster applications of AVs which are promising from a societal point of view and to take these developments into consideration during the decision-making process.
Definition and function of automation
Automation in this study refers to the transport system including all of its components, such as vehicles, drivers, users, infrastructure, information systems and applications. The level in which the driver is still ‘in the loop’ is used in order to discriminate between the different levels of vehicle automation: driver assistance (level 1), partial automation (level 2), conditional automation (level 3) and high/full automation (level 4).
In this study, our aim is to analyze strengths, weaknesses, opportunities and threats related to different applications of automation for autonomous private vehicles, freight transport and handling, and public transport. The potential of different applications of AVs in the Zuidvleugel in this study is strictly considered from a societal perspective (demand driven), in which AVs have a societal contribution to answer challenges the Zuidvleugel will face the upcoming years. Each application of automation is analyzed based on its functional ability to contribute to more agglomeration power of the Randstad Zuidvleugel, which in turn can improve the position of the Randstad Zuidvleugel relative to other European metropolitan areas.
Conclusions
We can conclude that a variety of (developments of) applications of automation exist in the Netherlands and worldwide regarding autonomous vehicles, freight and public transportation. We see several opportunities for the Zuidvleugel to benefit from these developments. Some of them are relevant for the short term (4 years), whereas other developments need more time to may be applied.
Read more: Essay TU Delft and Presentation workshop automated vehicles
Short Courses in Public Transport Planning
A practical guide to strategic and operations planning, network design, economic, appraisal methods, data collection, performance measurement, market forecasting and priority for bus, tram and rail services. in association with the Delft University of Technology, Dept. Transport&Planning, Institute of Transport Studies Monash University Iand Transport Research Centre, University of Auckland.
The first succesful trainings were held 26 January to 30 January, 2015 in Delft.
Part I
A practical guide to operations planning, market forecasting and economic appraisal methods for the development of bus and tram services. Key issues addressed at this short course are: Frequency determination; Timetable development; Vehicle scheduling; Demand forecasting; Service reliability management: Financial and economic appraisal of transit route development projects: Performance measures.
Part II
A practical guide to strategic and operations planning, network design, data collection, performance measurement and priority design for bus, tram and rail services. Key issues addressed at this short course are: Strategic perspectives; Network and route design; Data collection and analysis; Interaction with land-uses; Route choice and passenger flow forecasting; Priority for on-road public transport; Operations planning and crew scheduling; Network structure analysis.
Find more information here
Light rail implementation: success and failure aspects of Dutch light rail projects
Light rail has been successfully implemented in many urban regions worldwide. Although light rail has been a proven transport concept in many cities, there is much debate on the (societal) cost-benefit ratio of these systems. In addition to the success stories, several light rail projects were not that successful or even failed. In recent years, many light rail plans have been cancelled in The Netherlands, some after many years of planning and some even after the start of the tendering process or during trial operation. We want to know why this happened, so we will be able to support future design and decision making. This paper describes our research aiming at the answer to the question: what are the success and failure factors of light rail planning based on the Dutch experiences? This research has been performed as a survey, in which we investigated five projects, being light rail projects in the Netherlands (and one reference project in France) that either succeeded or failed in different project stages. The main conclusion is that several, multidisciplinary factors make a success or failure out of a light rail project. Projects do not fail just because a lack of funding, small political support or technical obstacles only. Rather than that, a combination of factors causes projects to fail. Subsequently, projects will only be successful if they are based on more than one success factor. Just a high potential ridership or political support is for instance not enough to guarantee a project to succeed.
Read the paper: TRB2015
Short term ridership prediction in public transport by processing smart card data
Public transport operators are exposed to massive data collection from their smart card systems. In the Netherlands, every passenger needs to check in and to check out, resulting in detailed information on the demand pattern. In buses and trams, checking in and checking out takes place in the vehicle, providing good information on route choice. This paper explores options for using this smart card data for analysis and performing what-if analyses by using transport planning software. This new generation of transport demand models, based on big data, is an addition to the existing range of transport demand models and approaches. The intention is to provide public transport operators with a simple (easy to build) model to perform these what-if analyses. The data is converted to passengers per line and an OD-matrix between stops. This matrix is assigned to the network to reproduce the measured passenger flows. After this step, what-if analysis becomes possible. With fixed demand, line changes can be investigated. With the introduction of an elastic demand model, changes in level of service realistically affect passenger numbers. This method was applied on a case study in The Hague. We imported the smart card data into a transport model and connected the data with the network. The tool turned out to be very valuable for the operator to gain insights into the effect of small changes.
Read the paper: TRB 2015
EMTA Report: Light rail explained
The need for viable, cost effective and attractive public transport in high-density areas is immanent. Transport Authorities have a responsibility to foster innovations in urban transport and look at smart replies to match the growth of demand for quality mass transit. A good living climate, economic efficiency, social inclusion, sustainability and competitiveness depend on the capacities of a city to invest in high quality transport services. The authors of this paper explain what especially in urbanised areas should be main reasons to persuade cities to improve accessibility and liveability by engage and develop a light rail solution. It comes down to a very basic question: “why light rail?” or more in general “why chose for high quality public transport?”.
In a thorough evidence-based description Rob van der Bijl and Niels van Oort demonstrate how it has been overlooked that light right rail does not only provide benefits that are obvious to all, like speed and comfort,
but that in cost-benefit terms also reliability of service should be valued in money. Efficiency benefits
thereby are incomplete and therefore impeded chances on smart light rail realisation. If taken into
account the social context of projects and awareness of the influence of the difference in types of
legal context, governance and institutional legacy a transformation of urban networks by light rail
can be an asset to spatial urban revival. The Light Rail can be an impetus to the urban quality of
life and more importantly provide a sustainable way of accommodating mobility needs of city
denizens and visitors.
Read the full report: EMTA Report
Data driven optimisation of public transport
Presentation at EMTA meeting at TfL in London:
Feedforward mechanisms in public transport; How data improves service quality and increases efficiency.
Find the presentation HERE
International Workshop on Utilizing Transit Smart Card Data for Service Planning
Collecting fares through “smart cards” is becoming standard in most advanced public transport networks of major cities around the world. Using such cards has advantages for users as well as operators. Whereas for travellers smartcards are mainly increasing convenience, operators value in particular the reduced money handling fees. Smartcards further make it easier to integrate the fare systems of several operators within a city and to split the revenues. The electronic tickets also make it easier to create complex fare systems (time and space differentiated prices) and to give incentives to frequent or irregular travellers.
Less utilised though appear to be the behavioural data collected through smartcard data. The records, even if anonymous, allow for a much better understanding of passengers’ travel behaviour as various literature has begun to demonstrate. This information can be used for better service planning.
First International Workshop on Utilizing Transit Smart Card Data for Service Planning; 2nd – 3rd July, 2014; Gifu, Japan
My contribution to the workshop: Short term public transport modelling using smart card data
Improved public transport by data driven research
New promising Big Data sources are becoming available in the public transport industry. This data provides insights into both passenger flows and vehicle performance and is of great help to optimize public transport services. Traffic models are able to quickly process this data and to present it on a geographical layer. It enables to evaluate ridership and to compare it with the use of other modes as car and bike traffic. Finally, what-if predictions are available to gain insights into the expected level of cost coverage, service and ridership. These steps are of great support to optimize the public transport network and timetable design as well as its operations. This presentation reveals such opportunities for public transport systems.
Read more:Presentation seminar “Analytics and Scheduling in Public Transport”