How does zero-fare public transport fare?

What are the implications of providing public transport without charging fees from users? Together with Yusak Susilo and Triin Reimal form KTH Royal Institute of Technology in Sweden, we evaluated the impacts of free-fare public transport policy by investigating the case of Tallinn, the capital of Estonia. The city introduced a free-fare public transport policy in January 2013 and became the largest city in the world so far to offer free-fare services to all of its inhabitants. While previous implementations of similar measures shed some light on the anticipated impacts of such a policy, there is lack of analysis which limits its validity. The case of Tallinn is a full-scale experiment that provides a unique opportunity to empirically evaluate economic, social, mobility and level-of-service aspects.

In the first phase of the policy evaluation, we conducted a macro-level empirical analysis of service performance, passenger demand and accessibility for various travelers’ groups. The results indicate that the the free-fare policy accounts for an increase of 1.2% in passenger demand with the remaining increase (1.8%) attributed to  extended network of public transport priority lanes and increased service frequency. The relatively small effect could be explained by the previous price level (36% free + 24% concessions) and public transport share (40%) as well as the consideration of the short-term impact. The evidence-based policy evaluation is instrumental in supporting policy making and facilitating the design of public transport pricing strategies. I discussed our findings in an interview to Citiscope, an urban magazine, which is available here.

The full article where we report our findings is available here. The paper includes a discussion on the transport economy theory and practical arguments for and against the scheme, lessons from previous experiences from which Tallinn clearly differs, a model that accounts for supply changes, an estimation of the elasticity of service frequency and reflecting on the economic viability of this scheme.

In the ongoing second phase of this study, we analyze detailed travel diary that a large sample of Tallinn residents reported directly before and a year after public transport became zero-fare in Tallinn. This will enable to analyze how the policy influences individual travel patterns, modal choice and accessibility. Moreover, we assess changes in mobility patterns for different user groups to find how fair the zero-fare policy is. If you are interested in taking part in this project drop me an email (see about page)!

 

 

hEART 2014

The hEART2014 conference – the 3rd Symposium of the European Association for Research in Transportation was concluded today after 3 days of presentations and discussions in Leeds, UK. I have attended all three hEART conferences that have been organized so far and they have all proven a good opportunity to discuss ongoing works within an interesting research community.

I had two contributions on this conference. The first one is concerned with the evaluation of capacity increase in public transport projects. Many public transport investments are motivated by the need to relief congestion. However, conventional static assignment models that are used for cost-benefit analysis are not suitable for assessingi congestion related benefits as most of the negative conogestion impacts arise from system dynamics (e.g. reliability, crowding and denied boarding) and are therefore not reflected in average volume over capacity levels. Together with Jens West and Jonas Eliasson, we applied a new appraisal scheme for a metro line in Stockholm which takes into consideration the dynamic congestion effects and their variations. The presentation slides are available here: Appraisal of increased pt capacity hEART2014.

The second contribution is an attmept to infer the urban structure based on transport flow data. The availability of pervasive data collection facilitates the analysis of spatial and temporal distribution of activities based on people movements rather than based on land-use density proxies (as is conventionally done in urban planning and trip generation models). Together with Qian Wang and Yu Zhao, we formulated a spatial analysis technique to identify urban clusters and then classify them based on their temporal profiles with respect to incoming and outgoing flows. We applied this technique to Stockholm metropolitan area using public transport flow data. The analysis provide insights on the discrepency between the planning policy and the observed urban structure. This technique might be most valuable for anlayzing urban forms in mega-cities in emerging economies which undergo rapid changes. The presentation slides are avialable here: Urban clusters

 

Two short courses in planning public transport

TU Delft organizes two short courses on planning and operating public transport systems. The courses will be held on 26-28 and 28-30 January, 2015 and will take place in Delft, The Netherlands. Together with international public transport experts, Avi Ceder, Graham Currie and Niels van Oort, the courses are designed as practical guides to strategic and operations planning, network design, economic appraisal methods, data collection, performance measurement, market forecasting and priority for bus, tram and rail services. The first course will be dedicated to planning at the route level while the second course considers planning at the network and strategic level. The short courses are designed for practicing public transport professionals, those involved in the transport and planning industry who have an interest in public transport planning and early stage researchers in the public transport domain.

For more information, the full program and registration, see the course website: http://www.ppts2015.org/ 

 

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Where should service reliability be regulated?

It is common practice among public transport operators to regulate service departure times at several locations along each route. These locations are often called ‘time point stops’. Departure times from these stops are regulated in order to improve the overall service reliability. The operator has thus to decide which and how many stops along the line would be used as time point stops. This may seem like a simple problem but for a line with 33 stops there are more than 8.5 billion possible solutions (8,500,000,000)! Too many time point stops is difficult to operate and can slow down the service while too few will not be sufficient to prevent the deterioration of service reliability along the line. In order to address this problem of selecting time point stops with the objective to minimize total passenger travel times as well as operational uncertainty, an meta-heuristic optimization method was applied using a simulation model. The results show that the time point stops selected by the operator in the case study were worse than choosing them by chance! This method could be easily applied for other services to yield better reliability performance with very simple means.

 

Click here to read the full paper.

 

What are the key factors influencing individual door-to-door travel satisfaction?

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The importance of the whole door-to-door journey and its implications on travelers’ experience is well-acknowledged. However, travel satisfaction is often measured and assessed with respect to single trip stages (e.g. bus ride), neglecting the effects of a multi-stage journey and trip complexity on overall traveler experience and satisfaction. This could potentially underrate the impact of the quality of interchanges and last-mile facilities on overall travel satisfaction. In order to address this issue, Yusak Susilo from KTH, Sweden and I conducted a study which investigated the key factors influencing individual travel experiences for different travel modes and at different trip stages, and how satisfaction with the access and egress stages relates to overall trip satisfaction.

The dataset that was used in this study was constructed based on a survey that was carried out in April and May 2013 in eight European cities: Bucharest (Romania), Coventry (United Kingdom), Dublin (Ireland), Rome (Italy), Stockholm (Sweden), Turin (Italy), Valencia (Spain) and Vilnius (Lithuania). This study was part of a pilot survey stage of the EU FP7 METPEX (A MEasurement Tool to determine the quality of the Passenger EXperience) project. The objective of the pilot study is to empirically test which variables are most important for different groups of travelers. The expected output of the METPEX project is to produce a list of key determinants of travel satisfaction variables which will be integrated into a real-time satisfaction measurement tool and can be used for benchmarking purposes at European-wide level. Read the full article here: http://www.sciencedirect.com/science/article/pii/S0965856414001827 

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