Buses are the most critical part of urban-rural transit systems. However, bus transit services in urban-rural areas face a trade-off between the need for better services and the low profitability resulting from low travel demand. In this study, we show that we can improve the utilization and profitability of urban-rural buses by merging freight transportation with passenger transportation. We developed a mixed-integer program to model and analyze the coordination between freight and passenger transportation in an urban-rural transit system. We then conducted a case study to evaluate the effectiveness of the proposed approach. The numerical results indicate that the consolidation of passenger and freight transportation significantly reduces the operation cost of logistics companies and improves the profit of bus companies. We finally discuss the consolidation's positive impacts on logistics companies, bus service providers, and society.

Social cost-benefit analysis is often used to analyse transport investments, and can also be used for transport operation planning and capacity allocation. If it is to be used for resolving capacity conflicts, however, it is important to know whether transit agencies' timetable requests are consistent with the cost-benefit framework, which is based on passenger preferences. We show how a public transport agency's implicit valuations of waiting time and crowding can be estimated by analysing timetables, apply the method to commuter train timetables in Stockholm, and compare the implicit valuations to the corresponding passenger valuations in the official Swedish cost-benefit analysis guidelines. The results suggest that the agency puts a slightly lower value on waiting time and crowding than the passenger valuations codified in the official guidelines. We discuss possible reasons for this and implications for using cost-benefit analysis for capacity allocation. We also find that optimal frequencies are more sensitive to the waiting time valuation than to that of crowding.

Railway markets in Europe have been reorganized to allow competition between different operators. Thus, European railways have been vertically separated, separating infrastructure management from provisions of train services. This allows several train operators to compete for passengers and freight services. Different ways have emerged for vertical separation, capacity allocation and track access charges. This paper reviews, compares and discusses important deregulation aspects, using examples from a number of European countries to show different possible solutions. The study describes how competition has been introduced and regulated, with a particular focus on describing the different ways capacity is allocated and how conflicting requests by different train operators are resolved. It also reviews the related issue of how access charges are constructed and applied. Although guided by the same European legislation, we conclude that the studied railways have different deregulation outcomes, e.g., market organization, capacity allocation. Besides, few countries have so far managed to create efficient and transparent processes for allocating capacity between competing train operators. Although allowed by the legislation, market-based allocation is absent or never used. In order to foster more competition which can yield substantial social benefits, the survey indicates that most European railways still need to develop and experiment with more efficient and transparent capacity allocation procedures.

Historiska data visar att vi i genomsnitt lägger ungefär en timme per person och dag på att resa, oavsett samhällets förändringar. Vi gör därför klokt i att inte hänga upp vår klimat-, miljö- eller transportpolitik på förhoppningen att resandet kommer att minska efter pandemin, skriver professorn i transportsystem Jonas Eliasson.  

Passenger origin–destination data is an important input for public transport planning. In recent years, new data sources have become increasingly common through the use of the automatic collection of entry counts, exit counts and link flows. However, collecting such data can be sometimes costly. The value of additional data collection hence has to be weighed against its costs. We study the value of additional data for estimating time-dependent origin–destination matrices, using a case study from the London Piccadilly underground line. Our focus is on how the precision of the estimated matrix increases when additional data on link flow, destination count and/or average travel distance is added, starting from origin counts only. We concentrate on the precision of the most policy-relevant estimation outputs, namely, link flows and station exit flows. Our results suggest that link flows are harder to estimate than exit flows, and only using entry and exit data is far from enough to estimate link flows with any precision. Information about the average trip distance adds greatly to the estimation precision. The marginal value of additional destination counts decreases only slowly, so a relatively large number of exit station measurement points seem warranted. Link flow data for a subset of links hardly add to the precision, especially if other data have already been added.

During the pandemic, passenger transport has decreased dramatically due to restrictions and recommendations to avoid social contacts. Hopes and expectations have been raised that experiences, habits and improved digital services developed or discovered during the pandemic can lead to a permanent decrease of travel volumes even in the long run, thereby reducing emissions, noise and congestion. This paper discusses this question, based on descriptive analyses of historical development of travel distances and travel times in Sweden, including a description of how transportation changed in Sweden during the pandemic. Obviously, it is too early to give a conclusive answer regarding long run effects, but judging from historical experiences of previous improvements in transportation and communication, it seems unlikely that increased digital experience, improved digital services or changed habits will lead to permanently reduced travel volumes. It appears more likely that improved digital services and increased digital maturity will continue to transform work, shopping and leisure, but that this will not translate into decreased physical travel to any large extent.