Articles

Transport energy conservation research in urban transport systems dates back principally to the Organization of the Petroleum Exporting Countries’ (OPEC) “Arab Oil Embargo” (1973–1974) and the Iranian revolution (1979), when global oil supplies became threatened and costs rose steeply. Two subsequent Gulf Wars (1991 and 2003) highlighted the dangerous geo-political dimensions of Middle-Eastern oil. In latter times, the urgency to reduce global CO2 output to avoid catastrophic climate change has achieved great prominence. How to reduce passenger transport energy use therefore remains an important goal, which this paper pursues in ten Swedish cities, based on five scenarios:

(1) increasing the relatively low public transport (PT) seat occupancy in each Swedish city to average European levels (buses 35%, light rail 48%, metro 60% and suburban rail 35%);
2) doubling existing PT seat occupancy in each Swedish city;
3) increasing existing car occupancy in each Swedish city by 10%;
(4) decreasing existing energy use per car vehicle kilometer by 15%;
(5) increasing existing modal split for daily trips by non-motorized modes to 50% in each city.

A sixth “best-case scenario” is also explored by simultaneously combining scenarios 2 to 5. The data used in the paper come from systematic empirical research on each of the ten Swedish cities. 

Intermodality or combining more than one transport mode during a single trip has been put forward to facilitate a modal shift from private car to more environmentally friendly modes such as public transport, cycling or walking. Bike-and-ride – that is, integrating cycling and public transport in one trip – is an attractive combination, as cycling as an active and clean mode is faster than walking and more affordable and flexible than other alternative modes of transport. Using cycling as a feeder mode to public transport could potentially allow people to reach more opportunities and improve their mobility, and ultimately, their well-being. Therefore, it is relevant to investigate the inequalities in access to bike-and-ride options across population groups. In this context, we suggest assessing the inequalities in bicycle access to the main transport hubs of a city by developing a composite indicator based on accessibility measures and the Theil index of inequality. This indicator captures the role of both private and public bikes – part of a Bike Sharing System (BSS) – in accessing the existing public transport system. The novelty of our approach lies in bringing the distributional justice perspective in the accessibility evaluation of transport and analysing the inequalities within and between any arbitrarily defined population groups. Moreover, in addition to travel time by bike, this accessibility measure incorporates a series of bike-related features, such as the typology of bike lanes (separated from or shared with roads), the presence of a BSS in the network, and bike facilities (e.g., parking racks) in transport hubs. The proposed methodology is applied to a real case study of the city of Malmö, Sweden, to prove its efficacy and usefulness. In particular, we examine how the level of bicycle access to the major public transport destination (including train stations and regional bus hubs) varies across the population. While considering the contextual properties of the city of Malmö, the inequalities are analysed in relation to spatial dimension and social background of the population, it is possible to extend the proposed analysis by including further features of the population, such as income or gender, and apply the same approach to different contexts.

In this chapter we show and analyse the aggregated trends in the Swedish public transport sector regarding demand, supply, costs, fares and car use. As a complement, we analyse public transport use and satisfaction from two cities that have adopted different strategies and measures to increase public transit use. The chapter aims at summarizing lessons learned from development of the Swedish public transport sector.

We compare the optimal public transport subsidies for a representative bus corridor in a small city and in a big city in Sweden, derived by assuming optimal pricing, frequency, bus stop spacing, and bus lane policies. The optimal cost-recovery of the buses depends on the relative size of two costs: waiting time and crowding/congestion. In the big city the high crowding cost is dominating, approaching full cost-recovery in the first-best optimum. In the small city the waiting time dominates, implying larger optimal subsidies. The subsidy is also more effective as a redistribution policy in the small city. 

Do small cities need more public transport subsidies than big cities?

This paper optimises the number of bus stops, and prices for car, bus and cycling in the busiest inner city corridor in Stockholm. We adopt the representative consumer approach and calibrate the current equilibrium using the quasi-linear utility function. We find that the number of bus stops is already close to optimal. Welfare would increase if the peak frequency was increased, if the bus fares were lowered and differentiated between long trips and short trips and, and that the toll for longer car trips was increased. The optimal toll for cyclists, and the welfare benefit from it, is small and does not compensate the transaction costs. The distributional effects of bus fare changes and higher car tolls are small because on one hand, high income groups place more value on travel time gains, but on the other hand, low income groups travel less frequently by car. Surprisingly, we find that in the welfare optimum, the bus service only requires a small subsidy due to congestion in the bus lane, crowding in the buses, and extra boarding and alighting time per passenger. The Mohring effect is limited because the demand, and thereby the baseline frequency, is already high.

This paper develops a methodology for testing and implementing differences in preferences for a set of public transport modes, relating to observed and unobserved attributes, in state-of-practice large-scale travel demand models. Results of a case study for commuters in the Stockholm public transport system suggest that there are preference differences among public transport modes. We found that the value of time for train is lower than for bus and metro, and that it is higher forauxiliary modes than for the main mode. Surprisingly, we found no evidence for differences proportional to the in-vehicle time between bus and metro, suggesting that characteristics of in-vehicle time in these two modes are valued equally by the travellers. Nevertheless, unobserved preference for metro is higher than the preference for bus. Regarding the existence of a rail factor, we find evidence to support the hypothesis that rail-based modes have in fact a smaller time parameter (train) or higher alternative specific constant (metro), indicating that rail modes are preferable to bus, ceteris paribus.

Many public transport services are heavily subsidized. One of the main justifications is the expected beneficial effect on road congestion. Stockholm introduced congestion pricing in 2006 and the effects on car and public transport demand were carefully monitored. The change in prices provides unique estimates on price- and cross-price elasticities. This paper uses these data to model how the optimal pricing, frequency, bus size and number of bus lanes for a corridor depends on the presence of congestion pricing for cars. Results show that the presence of road pricing makes the current subsidies for peak bus trips too high. However, the major welfare benefits of re-optimizing the current bus supply stem from a decrease in frequencies during the off-peak period and the use of larger buses.

Urban experimentation and testbed planning have emerged as a response for developing solutions to contemporary urban challenges and constitute designated spaces of risk-taking. They represent strategic attempts at reimagining, influencing and even altering urban futures through the specific focus of being open to surprises and the unexpected. The aim of this article is to conceptualize risk in testbed planning and analyze risk and urban planning approaches to risk-taking. By using mobility experiments in five Nordic municipalities, it is shown that three approaches to risk prevail with regard to different loci of risk in testbed planning. These three approaches are minimizing and shifting responsibilities for individual risk, minimizing and shifting organizational risks and refusing political risks.

Due to relatively low patronage levels, rural bus stops are sometimes questioned in order to improve travel time and reliability on regional bus services. Previous research into stop spacing has focused on urban areas, which means that there is a lack of knowledge regarding the effects of bus stops in regional networks, with longer distances, higher speeds, and lower passenger volumes, in general. The present study addresses this knowledge gap by analysing the effects of bus stops on a regional bus service regarding average travel times, travel time variability, and on-time performance. This is done by statistical analysis of automatic vehicle location (AVL) data, using a combination of methods previously used for analysis of rail traffic and urban bus operations. The results reveal that bus stops that are only used sporadically have a limited impact on average travel times, in general. In contrast, they are all the more influential on travel time variability, and, in turn, on on-time performance. On the studied bus service, the number of stops made have a far greater impact on travel time variability than any of the other included variables, such as the weather or traffic conditions during peak hours. However, the results suggest that rural bus stops have a much lower impact than what we define as secondary bus stops in urban areas. Consequently, by primarily focusing on bus stop consolidation in urban areas, it is possible to significantly improve service reliability without impairing rural coverage.

Having access to realistic and empirically grounded passenger valuations of public transport trip components facilitate the undertaking of necessary trade-offs during planning of transport networks. Discrete choice estimation of path choice preferences is a practical way to obtain such preferences. This paper proposes a new take on the empirical foundation of path choice estimation based on revealed choices by introducing trip data for full activity-based ‘door-to-door’ public transport trips collected from a dedicated survey application for smartphones. Choice probabilities were modelled based on an explicitly generated choice set, where the public transport trip parts were generated using a branch-and-bound approach. Results in terms of estimated preferences are comparable to those based on conventional surveying methods and suggest significant premiums for paths involving public transport stops with an elevated level of passenger service as well as differences in preferences across population groups.