Punctuality is an important aspect of train operations, highly valued by passengers. Both Swedish and Norwegian railways have introduced frameworks to systematically improve punctuality in their systems, inspired by an extensive literature on Total Quality Management. After about a decade with these frameworks, we can see that punctuality has risen by about 2-3 percentage points. However, this pace of improvements is slower than desired. We propose that there is a gap between what most individual improvement efforts deliver, and what can be detected by directly monitoring punctuality. This gap stifles the desired culture of constant improvements. We instead propose a methodology for how to monitor punctuality improvements, by focusing on the constituents of a train trip. Using 20 years of data from commuter trains in three metropolitan regions (Stockholm, Gothenburg & Malmo), we show the frequency of runtime and dwell time delays is directly related to punctuality. These delay frequencies are also easy to measure and target, and more easily capture the intended effects of specific improvement efforts. Our hope is that this framework and measures such as these will better enable systematic efforts to improve railway punctuality.

In this paper we develop two methods for the use of mobile phone data to support the estimation of long-distance mode choice models. Both methods are based on logit formulations in which we define likelihood functions and use maximum likelihood estimation. Mobile phone data consists of information about a sequence of antennae that have detected each phone, so the mode choice is not actually observed. In the first trip-based method, the mode of each trip is inferred by a separate procedure, and the estimation process is then straightforward. However, since it is not always possible to determine the mode choice with certainty (although it is possible in the majority of cases), this method might give biased results. In our second antenna-based method we therefore base the likelihood function on the sequences of antennae that have detected the phones. The estimation aims at finding a parameter vector in the mode choice model that would explain the observed sequences best. The main challenge with the antenna-based method is the need for detailed resolution of the available data. In this paper we show the derivation of the two methods, that they coincide in case of certainty about the chosen mode and discuss the validity of assumptions and their advantages and disadvantages. Furthermore, we apply the first trip-based method to empirical data and compare the results of two different ways of implementing it. © 2021 The Authors

Connection trips is often an important part of long-distance travel, especially for air travel. Models of long-distance travel would therefore benefit from a more detailed representation of the connection part. In this paper it is however shown that most models of connection trips are stand-alone models not integrated with the model for main mode. Only a handful models that integrate connection trip modelling into a large-scale transport model for long-distance travel are found. The connection trip models are classified into different types using a typology developed within the paper. The typology identifies nine model types that differ in how access/egress mode choice and terminal choice are handled. The scarce literature on connection trip modelling within large-scale transport modelling systems call for more research regarding detailed representation of access/egress mode choice and terminal choice, especially regarding the trade-off between model complexity and detailed representation, as well as whether the detailed representation of connection trips should primarily be conducted within the public transport network assignment or on the demand modelling side.

This paper presents an analysis of the potential impacts of large-scale adoption of driverless trucks on transport patterns and system costs for a national freight transport system with Sweden as a case study. The analysis is performed by extending the application domain of the Swedish national freight transport model Samgods to analyze two types of driverless truck scenarios. The first scenario represents a full adoption of driverless trucks that can operate the complete road network and thereby substitute manually driven trucks. In this scenario, road transport tonne-kilometers on Swedish territory increase by 22%, vehicle kilometers traveled by trucks increase by 35% and annual total system costs decrease by 1.7 B€ compared to a baseline scenario without driverless trucks. In the second scenario, the current fleet of manually driven trucks is complemented by driverless trucks that can operate on major roads between logistics hubs, but not in complex traffic environments like urban areas due to a limited operational design domain. This may be an initial use-case for driverless trucks operating on public roads. In this scenario, road tonne-kilometers increase by 11%, truck vehicle kilometers traveled increase by 15%, and annual total system costs decrease by 1.2 B€ compared to the baseline. For both scenarios, the impacts of driverless trucks vary significantly between commodity types and transport distances which suggests heterogeneity of benefits of automated driving between different types of freight flows. A sensitivity analysis is performed in which the costs for driverless truck operations is varied, and for the second scenario, also which parts of the road network that driverless trucks can operate are varied. This analysis indicates that the magnitude of impacts is highly dependent on the cost level of driverless trucks and that the ability for DL-trucks to perform international, cross-border transport is crucial for achieving reductions in system costs. An overarching conclusion of the study is that driverless trucks may lead to a significant increase in road transport demand due to modal shifts from rail and sea as a result of the improved cost performance of road transport. This would further strengthen the need to decarbonize road transport to meet non-negotiable climate targets. Important topics for future research include assessing potential societal costs related to driverless trucks due to infrastructure investments and negative externalities such as increasing CO2 emissions and congestion. © 2021 The Authors

In this paper, we show that cost variation for long-distance travel is often substantial and we discuss why it is likely to increase further in the future. Thus, the current practice in large-scale models, to set one single travel cost for a combination of origin, destination, mode, and purpose, has potential for improvement. To tackle this issue, we develop ways of accounting for cost variation in model estimation and forecasting. For public transport, two approaches are proposed. The first method focusses on improving the average fare, whereas the second approach incorporates a submodel for choice of fare alternative within a demand model structure. Only the second method is consistent with random utility theory. For car, cost variation is related to long run decisions such as car type choice. Handling car cost variation therefore implies considering car type choice. This long-term choice can be considered using a car fleet model. © 2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

We explain the rationale for congestion charges in congested cities. We review the existing congestion charging systems in the world and their design. We show that congestion charges have proven to be efficient in reducing congestion in the long run. Hence, it works. However, we also show that congestion reduction cannot be taken for granted, it demands a good design of the system. A poor system design can easily deteriorate the traffic situation, by causing second-best problems. To develop an efficient system design, using a good, calibrated state-of-practice transport model is key. We end the chapter by discussing why are congestion charges so rare in the world. This has mainly to do with difficulties of building long-term public and political support. These depend to a large extent on the power over the revenues.

Sampers är det nationella modellsystemet för att analysera persontransporter i Sverige och används vid trafikslagsövergripande analyser (Trafikverket 2018). Sampers består av två hittills separata modeller – en för regionala resor och en för långväga resor över 100 km. Regionala och långväga modellerna har olika ingående färdmedel (cykel och gång finns inte i långväga och flyg finns inte i regionala modellen), olika zonsystem, olika ingående ärenden etcetera. Att på detta sätt ta fram separata modeller för regionala och långväga resor är vanligt och görs t. ex. även i Norge och Storbritannien. Geografiskt mindre länder så som Nederländerna och Danmark analyserar regionala och långväga resor i samma modell, men behöver då ta särskild hänsyn till skalningseffekter (Rich and Hansen 2016). I modeller så som Sampers där resor delas in i två segment – regionala och långväga – kommer frågan upp hur anslutningsresor till långväga resor bör hanteras.

Att få en bättre modellering av anslutningsresande i Sampers vore önskvärt av flera anledningar. Efter en bakgrund och motivering till varför bättre modellering av anslutningsresande behövs, fortsätter rapporten genom att i Kapitel 2 beskriva rapportens syfte. Kapitel 3 ger sedan en beskrivning av den typologi som vi utvecklat för klassificering av anslutningsrese-modeller. I Kapitel 4 redovisas resultaten från genomförd litteratursökning och Kapitel 5 avslutar med att diskutera lärdomar och överväganden inför vidareutveckling av Sampers långväga modell.

Den här rapporten är en del i ett forskningsprojekt där vi studerar det svenska anslutningsresandet. Här beskrivs anslutningsresor med data från svenska nationella resvaneundersökningen. Ungefär 35 procent av alla långväga (mer än 10 mil) resor sker med ett färdmedel som förutsätter en resa till en station eller flygplats. De flesta långväga resor har en mycket enkel struktur med korta anslutningsresor till huvudfärdmedlet. Det är ovanligt med fler färdmedel under en resa förutom huvudfärdmedel, anslutande och avslutande färdmedel. Anslutningsfärdmedel och huvudfärdmedel är enkelt identifierbara i data. Det råder också en stor symmetri mellan utresa och återresa avseende både huvudfärdmedel och färdmedel för anslutningsresa. För flygresor utgör anslutningsresan ofta under 10 % av resans totala längd men 30% till över 50 % av reseuppoffringen. Anslutningsresan utgör således en signifikant del av den totala reseuppoffringen både i tid och pengar för flyg medan restiden och biljettkostnaden för tåg är en mer komplett beskrivning av hela resan. Resor med tåg startar och slutar ofta i stadsmiljö med närhet till många målpunkter och relativt stort utbud av kollektivtrafik. Det råder därmed en asymmetri i beskrivningen av reseuppoffringen mellan flyg och tåg när man inte tar hänsyn till anslutningsresan.

Cost-benefit analysis (CBA) for cycling infrastructure investments are less sophistically developed compared to the ones for private cars and public transport, and one of main reasons is the lack of “well-developed” transport models for cycling. In this study, a dedicated transport model for cycling is used to appraise cycling infrastructure investments in Stockholm, Sweden. The model captures the impact of a change in cycling infrastructure on cycling route choice, mode choice, destination choice and trip generation and calculates cycling flow on link level. the generalised cost measure defined in the route choice model captures the impact of cycling infrastructure. Results suggest that although cycling flow on the links with investment may increase substantially, only a small share comes from modal shift and thus the external effects such as reducing car congestion and emissions are marginal. For all three scenarios investigated, over 97% of the benefits measured in the unit of generalised cost belong to the existing cyclists. The route choice model does not minimize travel time but generalised cost which also measures health, safety benefits and other possible benefits that may be considered by the cyclists when they choose to cycle. In fact, travel time saving benefits of the investments evaluated in this paper are all negative. The existing effect evaluation models therefore need to be adjusted to be more consistent with the transport model.