A biased preference for the status quo could explain the increased support for policies following their implementation. However, the influence of status quo bias on support for transport policies has been analysed to a limited extent only. The counterfactual test serves as a potential method to empirically explore this influence by framing policies as the existing or alternative situation. This paper employs the counterfactual test to ascertain whether individuals disproportionately favour the status quo. To this end, we have designed separate experiments focusing on three transport policies: road pricing, speed limits, and train ticket fare differentiation. The results indicate that status quo bias does indeed influence support for transport policies. Participants prefer each policy option when framed as the status quo. In contrast, support for the same policy option declines when presented as the alternative situation. These findings underscore the irrational tendency to adhere to the status quo, which may stem from psychological commitments or cognitive misperceptions. Therefore, politicians, policymakers, and practitioners should anticipate a bias towards the status quo when introducing controversial transport policies.

Van februari 2003 tot januari 2025 werkte ik aan de TU Delft als hoogleraar Transportbeleid. Wat zijn belangrijke trends in ontwikkelingen, in onderzoek en beleid? Dit artikel geeft een beknopt en selectief overzicht van enkele dominante onderwerpen, met het accent op personenvervoer.

Based on three decades of personal experience this paper provides suggestions for researchers who consider to have contacts with policy makers, politicians, and the media (PPM actors). The point of departure is that such contacts may be beneficial for researchers and their institutes, as well as for policy making and wider society. The core of the paper is a set of ten recommendations. These recommendations focus on having contacts with PPM actors at all, and if so: under which conditions, discussing the questions to be answered, the importance of core messages, scientific underpinnings of answers, the storyline of answers, the different mindsets of researchers as opposed to PPM actors, avoiding criticizing politicians, the benefits for researchers of having contacts with PPM actors, and proactively contacting PPM actors.

This research investigates the influence of socio-cultural factors and sociodemographic characteristics on bicycle use in Auckland, a multi-cultural city in New Zealand. To identify the strength of socio-cultural factors compared to other various social psychological determinants, a conceptual model is proposed encompassing Socio-cultural influences, Price Value, Perceived Safety and Security, Perceived accessibility, Information and Engagement, and Bicycle use. Using Structural Equation Modelling (SEM), the effects of these determinants on bicycle use were assessed. The moderating effects of sociodemographic factors including age, gender, ethnicity, and income level on the influence of these determinants on bicycle usage were also examined. Results suggest that socio-cultural influences have the strongest impact on bicycle use in Auckland, showing that those who ride a bicycle more than others are influenced more by family, friends, community, and culture to use a bicycle. Additionally, sociodemographic characteristics only moderate the influence of socio-cultural factors on bicycle usage indicating that socio-cultural factors influence bicycle use differently across various population groups. The strong influence of socio-cultural factors and the moderating role of sociodemographic characteristics on bicycle use in Auckland suggest that social and cultural dynamics are critical in shaping individual decisions to cycle, even more than practical considerations such as price, infrastructure, engagement, or safety. Therefore, transport strategies targeting specific population groups and relevant socio-cultural barriers can enhance bicycle use and promote equity in cycling. Suggested transport strategies include integrating socio-cultural initiatives with local government's transport policies such as education, community engagement, and awareness campaigns, implementing effective monitoring and evaluation initiatives followed by longitudinal investigations, and incorporating cultural representation in cycling initiatives. These short-term, mid-term, and long-term strategies can guide the development of more inclusive and effective transport strategies to enhance cycling participation across diverse demographic groups and achieve broader societal benefits.

The aim of this conceptual paper is to contribute to a better understanding of the front-end phase of large public projects, which is complex and non-linear. The point of departure relates to a number of paradoxes found along the way of the front-end. A processual approach is taken to follow the front-end over time. Considering a number of example vignettes, four paradoxes and subsequent trade-offs are discussed which affect the strategic decisions that need to be made. These are found to fit largely within four generic sub-processes identified in the front-end. Inspired from the paradox theory, we conceptualise paradoxes and trade-offs under the dynamic equilibrium model adapted for temporary organising such as large public projects. Main aim of this paper is to consider how decision-making can be improved, and managerial strategies developed that permit the acceptance of paradoxes and their resolution in a virtuous cycle leading to long term success.

This study explores perceived accessibility specific to air transportation in the Dutch context through a focus group study. Five focus group sessions were held with a total of 24 participants with air travel experience within the past five years. Online focus groups were held during the period that the COVID-19 pandemic travel restrictions were in effect, specifically around 12 months after the travel restrictions were implemented globally. In terms of the importance of activities accessible by flight, we observe that travelers particularly attach importance to visiting family and relatives, while the importance attached to the business and recreational activities accessible by flight varies among participants. As far as the transport component of accessibility is concerned, we find that, in addition to conventional variables in air transportation research, such as cost and travel times, unconventional variables such as uncertainty during flight schedule disruptions or the mood of staff and other passengers contribute to perceived accessibility by air transportation. Based on the results, we further discuss characteristics specific to perceived accessibility by air transportation, directions for further qualitative and quantitative research regarding perceived accessibility by air transportation, and implications for policy and planning.

As cities grow, the benefits of living in them are increasingly unequally distributed. USA cities, in particular, have experienced rapid suburbanization of poverty and decreased levels of access to jobs for transit-dependent and vulnerable communities. The public transit challenges in suburbs call for innovative forms of transit to turn the tide on urban inequality. On-demand microtransit, a novel type of shared mobility provides efficient, convenient and affordable transportation. Its potential for redressing inequity had yet to be investigated fully in a suburban setting. We presented a case study from the suburbs of Minneapolis-St. Paul in Minnesota, USA. We combined unique datasets of microtransit ridership from two public transit agencies, transit surveys, land use data, and expert interviews, to conduct spatial analysis, accessibility analysis, and equity impact assessments for these suburbs. We found that microtransit enables public transit agencies to reach a larger number of vulnerable riders than fixed-route transit, particularly for commuting and trips to/from commercial areas. Microtransit also provided a cheaper alternative to ride-hailing and a faster alternative to public transit and walking, without cannibalizing ridership from fixed-rout transit alternatives. Finally, microtransit redressed transportation inequities by alleviating access inequality, reaching vulnerable rider groups effectively, and creating travel opportunities that are less spatially concentrated than those provided by traditional, fixed-route public transit. This study provided a framework for further investigations into the impact of microtransit, including in urban core or rural settings, and highlighted the impact of microtransit in reducing access inequity in a suburban environment.

Car dependence brings along many negative social and environmental externalities that policymakers and stakeholders need to consider. Nonetheless, the concept is not well defined and lacks a clear framework regarding its determinants and mechanisms, which also leads to problems in terms of its operationalisation. Therefore, this paper proposes a conceptualisation and operationalisation of car dependence, which can serve as a basis for further research and policy. We define car dependence as the extent to which an individual is incapable to participate in location-based activities without a car in a satisfactory way. This definition is based on the theoretical background of the capabilities approach and the concept of motility and also linked to the concept of accessibility. Our conceptual model consists of seven components, most of which have been considered separately in previous conceptualisations, namely the land use system, transport system, natural environment, temporal component, social environment, and individual objective/subjective characteristics. These components range from being external to the individual (e.g. the land use system) to internal (e.g. individual features). Considering these components jointly emphasises the importance of looking at car dependence in a holistic, unifying way. This approach contributes to a better understanding of car dependence that goes beyond the explicit analysis of components in previous research. In addition, we provide a systematic approach to operationalising car dependence that contributes to a more comparable approach to measuring car dependence. Researchers have to decide whether they want to examine car dependence via its components or via self-report by individuals, whether they want to study the full set of components or only a subset, and whether they want to consider perceptions or factual information about external components. Therefore, our conceptualisation and operationalisation provide valuable new insights into car dependence regarding new research directions and policy approaches.

Car sharing contributes to reducing emissions, resource depletion, and land take, by promoting more efficient use of vehicles that on average sit idle 96% of the time. But consumer adoption remains limited. User segmentation studies can inform efforts to mobilize potential users to join car sharing, and to anticipate what their needs and usage characteristics will be. This paper proposes a comprehensive segmentation method based on socio-demographic variables, which reveals differences in preferences for car sharing platform type, usage characteristics and societal outcomes of car sharing use. To do so, we apply a three step Latent Cluster Analysis to a nationwide sample of active car sharing users. This method results in a set of user segments that reflect distinct life phases, with different needs in terms of the frequency and type of trips made by car sharing. This is reflected in different preferences for car sharing platform types, as the likelihood to use peer-to-peer car sharing as opposed to business-to-consumer car sharing differs by user segment. The segments do not differ substantially in their motivations for engaging with car sharing. Yet, environmental motivations for car sharing outrank financial motivations, while social motivations play no substantial role. The clusters do show substantial differences in the changes in car ownership that occur while being an active car sharing member as well as the likelihood to use car sharing in place of a private car rather than public transport or walking and biking. We conclude that a comprehensive segmentation method based on socio-demographic variables provides actionable insights for upscaling car sharing adoption, as well as targeting specific user segments in order to optimize societal outcomes from car sharing use.

This study aims to evaluate equity in cycling initiatives and their operational challenges by reviewing a wide range of cycling initiatives implemented in Auckland, New Zealand. The effectiveness of current initiatives with respect to various target groups or resulting beneficiaries is discussed, along with potential additional initiatives, barriers to implementing cycling equity initiatives in practice, and possible solutions to address such barriers. By interviewing policymakers, decision-makers, planners, designers, and transportation professionals, 44 cycling initiatives are identified. Results suggest that the geographical distribution of some of the current initiatives implemented could be more equitable. While some initiatives are equitable, there remain challenges with respect to their implementation. Additionally, there are limited initiatives focusing on the safety of female cyclists in Auckland, and no initiatives specifically aimed at Māori and Pacific people, groups that can both be considered disadvantaged with respect to cycling in Auckland. Potential additional policy initiatives include e-bike/bicycle subsidies, policy and law changes, education and awareness campaigns, better urban planning, policies aimed at making cycling easier, and better monitoring and evaluation. Barriers to the implementation of cycling equity initiatives in practice include sociocultural issues, financial constraints, poor planning, human resource limitations, and the built environment. Suggested strategies to help overcome some of these issues include adopting an equity lens and providing equity assessments for all initiatives, thus providing a wider coverage with respect to diversity in the population, enhanced engagement with the community, and the empowerment of people.

Latent Class Analysis was used on the 2018/19 Dutch National Travel dataset to assess travel behaviour profiles and its connection with sociodemographic and spatial factors to grasp travel patterns in a more holistic context than previous research

Smooth cycling can improve the competitiveness of bicycles. Understanding cycling speed variation during a trip reveals the infrastructure or situations which promote or prevent smooth cycling. However, research on this topic is still limited. This study analyses speed variation based on data collected in the Netherlands, using GPS-based devices, continuously recording geographical positions and thus the variation in speeds during trips. Linking GPS data to spatial data sources adds features that vary during the trip. Multilevel mixed-effects models were estimated to test the influence of factors at cyclist, trip and tracking point levels. Results show that individuals who prefer a high speed have a higher average personal speed. Longer trips and trips made by conventional electric bicycles and sport bicycles have a higher average trip speed. Tracking point level variables explain intra-trip cycling speed variations. Light-medium precipitation and tailwind increase cycling speed, while both uphill and downhill cycling is relatively slow. Cycling in natural and industrial areas is relatively fast. Intersections, turns and their adjacent roads decrease cycling speed. The higher the speed, the stronger the influence of infrastructure on speed. Separate bicycle infrastructure, such as bike tracks, streets and lanes, increase speed. These findings are useful in the areas of cycling safety, mode choice models and bicycle accessibility analysis. Furthermore, these findings provide additional evidence for smooth cycling infrastructure construction.

Air transportation is a mode of transport developed specifically to provide access to long-distance destinations that may otherwise be infeasible or at least more difficult to reach. Accordingly, there are distinct aspects of air travel that require consideration when assessing accessibility by air transportation, which are not addressed in general local accessibility studies. This paper reviews studies of accessibility by air transportation. The studies in question were published in academic journals, and we analysed them using the broad theoretical framework of accessibility of Geurs and van Wee [Accessibility evaluation of land-use and transport strategies: Review and research directions. Journal of Transport Geography, 12(2), 127–140]. We discuss the characteristics of accessibility by air transportation to consider when designing research, as well as trends and knowledge gaps in the existing literature. An important gap is that, while there is a growing interest towards perceived accessibility by air transportation, accessibility measures based on this perspective have not yet been applied yet. Additionally, the literature is largely focused on the transport and land-use components of accessibility as opposed to the individual and temporal components. We finish by discussing the benefits and drawbacks of directly applying conventional accessibility measures for research on accessibility by air transportation, as well as options to modify the temporal component of conventional person-based accessibility measures for better applicability in the air travel context.

Rapid urbanization has posed challenges to accessibility to critical services that require in-depth analysis. Complex networks theory has been used to evaluate the evolution of network topologies or the overall accessibility of transportation systems. However, topological metrics to explain the temporal changes in accessibility levels do not fully capture the dynamics and implications of accessibility to specific critical services. In this study, we address this gap and investigate the opportunities of using a self-avoiding random walk (SARW) algorithm to evaluate and explain the evolution of spatial accessibility to education facilities. We used hotspot analysis to understand the temporal changes and investigated changes in hot and cold spots over time. Furthermore, we explored the relationship between the network indicators and the SARW-based accessibility metric. We illustrated this method in a case study from Helsinki, where large-scale open data spanning from 1991 to 2016 is available. Our findings indicate that the SARW-based metric delivers more detailed node-level results than the traditional isochrone-based metric. The latter generates accessibility zones where accessibility is assumed to be uniform, while the SARW metric captures the dynamic nature of educational facility accessibility more accurately. The developed methodology helps to identify the impacts on the historical development of accessibility and can be applied to investigate accessibility to other critical services.

A restructuring of the current mobility and transportation system seems to be inescapable, as a result of the increasing urbanization and challenges regarding global sustainability. The concept of Mobility-as-a-Service (MaaS) is regarded by policy-makers as an answer to the needed change. Generally speaking, MaaS is an online platform that enables users to plan, book and pay a trip out of a variety of transport modes, conventional and shared. However, in the literature, the potential impact of MaaS on mobility is still relatively unclear. This study, therefore, aims to provide insights into which factors influence the intention to use MaaS among private vehicle owners, who have until now been identified as relatively MaaS-averse travellers. Policy-makers are highly interested in this group to start using MaaS since their shift from private vehicles to other transport options might positively contribute to easing the congestion and environmental problems. In order to create some insights on possible travel behavioural shift and adoption of new systems, an empirical study has been conducted among (co–)owners of motorized vehicles (passenger car, electric passenger car, van, motorcycle; moped) that live in the Netherlands. The survey was based on a conceptual model that explains why people would use this new system (MaaS) and has asked respondents about their travel behaviour, socio-economic characteristics and attitudes towards MaaS. Using Latent Class Cluster Analysis (LCCA) five clusters in the sample population regarding the intention to use MaaS were identified. The cluster profiles show that private vehicle owners who often use public transport and active modes are most inclined to use MaaS, whereas the ‘conservative’ passenger car owners who use the car as their main mode of transport for all their trips (e.g. commuting, leisure) show a lower intention to use MaaS. As it can be expected that the societal benefits of MaaS will especially occur when these conservative car owners adopt MaaS, we conclude that, from a policy perspective, implementing MaaS could be less effective in reducing transport externalities (e.g. pollution and wasted time in congestion) as perhaps expected.

After the outbreak of COVID-19 pandemic, crowding has been highlighted as a risk factor for contracting acute respiratory infections (ARIs) such as COVID-19, which has affected the demand for public transport. Although several countries, including the Netherlands, have implemented differential fare systems for peak and off-peak travel to reduce crowding during the rush hours, the problem of overcrowding on trains has remained prevalent and is expected to cause more disutility than even before the pandemic. A stated choice experiment in the Netherlands is conducted to understand the extent to which people can be motivated to change their departure time to avoid crowded trains during rush hours by offering them real-time information on on-board crowding levels and a discount on the train fare. To gain further insights into how travelers respond to crowding and capture unobserved heterogeneity in the data, latent class models have been estimated. Unlike the previous studies, the respondents were segregated into two groups before the start of the choice experiment based on their indicated preference to schedule a delay earlier or later than their desired departure. To study the change in travel behavior during the pandemic, the context of different vaccination stages was also provided in the choice experiment. Background information collected in the experiment was broadly categorized as socio-demographic, travel and work-related factors, and attitudes towards health and COVID-19. It was found that the coefficients obtained for the main attributes which were presented in the choice experiment (on-board crowd levels, scheduled delay and discount offered on full fare) were found statistically significant, and in line with previous research. It was concluded that when most of the people are vaccinated in the Netherlands, the travelers become less averse to on-board crowding. The research also indicates that certain groups of respondents, such as those who are highly crowd averse, and are not students, can be motivated to change their departure time if real-time crowding information was provided. Other groups of respondents who were found to value fare discounts can also be motivated to change their departure by similar incentives.

Transport models have been defined in many ways and there are various kinds of models. In this chapter, a model is defined as a simplified representation of part of reality. The main goal of models is to estimate the behaviour of the real system in different scenarios (see Chapter 14) in a specific forecasting year. Possible outputs of these models may be, for example, the number of passenger kilometres in a country, region or city in a certain year or, often combining transport models and impact models, societally relevant outcomes in the area of accessibility, safety or the environment, and increasingly health. Models are often used to get an insight into the behaviour of the system in a do-nothing scenario and/or to gain an insight into the effects of proposed measures/policies on transport and other system-related components such as land use. Usually, not one but several futures are predicted whereby the effects of transport are computed for several scenarios concerning the socioeconomic development and policy variants (see Chapters 14 and 15).

This chapter provides readers with an introduction to how models work and shows what they can be used for. This knowledge should enable the reader to form an opinion as to whether a specific model can be used to answer certain questions. This chapter is focused on what are often called ‘strategic models’. These are models that aggregate volumes of travellers for a faster representation of mobility patterns in a city, region or country. In contrast, models for reproducing traffic flows on highways intended for real-time traffic management require modelling each vehicle. They are presented in Chapter 7 and are not dealt with in this chapter. At specific places in the text, we may refer to other modelling levels for the sake of distinction and clarification. For further insights into transport modelling, the authors recommend the book by Ortúzar and Willumsen (2011).

Section 16.2 provides an overview of strategic models. Section 16.3 introduces the concept of elasticity which is used in many strategic models. Section 16.4 discusses the traditional strategic aggregated models, while disaggregated models are discussed in section 16.5. Section 16.6 deals with model validation. Section 16.7 presents some examples of models currently used in the Netherlands. Section 16.8 addresses the question of what can and cannot be done using models. The main conclusions of the chapter are presented in section 16.9.

Ensuring equity is considered in all types of decision making, including with respect to cycling provision, is important. Studies have investigated equity in relation to provision of cycling infrastructure and facilities. However, identifying other factors that need consideration in cycling equity is important. This study explored the impact of cycling infrastructure provision on individual perceptions of cycling infrastructure in relation to sociodemographic characteristics in Auckland, New Zealand. The results indicated that bicycle lane availability did not significantly influence perceptions of cycling infrastructure; however, ethnicity and whether a person was a regular cyclist did. Among noncyclists and potential cyclists, ethnicity was the only factor found to significantly influence perceptions of cycling infrastructure. Maori, the indigenous people of New Zealand, and Pacific Islanders rated the provision of cycling infrastructure higher than others for the same level of bicycle infrastructure in their community. Whereas Maori had the highest percentage of potential cyclists among all ethnicities, Pacific Islanders had the highest percentage of noncyclists (64.9%), the lowest percentage of potential cyclists, and one of the lowest percentages of regular cyclists. The study showed that cycling provision perceptions were more affected by factors like ethnicity, education, and bicycle user type than objective measures of bicycle infrastructure. Following the capabilities approach of justice, this study suggests that equitable provision of cycling infrastructure may not lead to an equitable cycling environment. To achieve this, interpersonal and intrapersonal indicators such as ethnicity and community-related factors must also be considered to encourage and empower all population groups to cycle.

Innovations in transportation can contribute to reaching relevant societal objectives (e.g. reduce emissions, congestion levels and/or risks). To determine which innovations to stimulate (and which not) it is important for policy makers to assess their effects on beforehand. Expert judgement is an often-used method for this purpose. Although expert opinions can provide useful input for decision-making, these judgement are potentially subject to change, for example, due to new information becoming available or because the (academic) discussion about the innovation in question takes a new turn. Studies that explicitly study stability and change in expert judgements are rare, but highly relevant to determine the reliability of experts' assessments. To address this gap, this study assesses experts’ judgments at multiple points in time focusing on the effects of a transport innovation with potentially widespread societal implications, namely Automated Vehicles (AVs). To this end a survey was administrated to a group of experts involved in the WISE-ACT project. The results indicate that expert opinions towards this innovation are generally favorable; AVs are believed to reduce congestion delays, greenhouse gas emissions and traffic accidents. Although the consulted experts are generally quite stable in their opinions, they are becoming less optimistic about these positive effects over time. A Q-factor analysis additionally reveals two clusters of experts, one with a positive and one a negative outlook on AVs. The latter group beliefs that AVs will lower the value of travel time, thereby increasing travel demand, and, in turn, emission and congestion levels. Overall, the changing and diverging opinions among experts indicate that the transition to AVs is not necessarily regarded as a desirable one.