Vulnerability analysis for large-scale and congested road networks with demand uncertainty

To assess the vulnerability of congested road networks, the commonly used full network scan approach is to evaluate all possible scenarios of link closure using a form of traffic assignment. This approach can be computationally burdensome and may not be viable for identifying the most critical links in large-scale networks. In this study, an “impact area” vulnerability analysis approach is proposed to evaluate the consequences of a link closure within its impact area instead of the whole network. The proposed approach can significantly reduce the search space for determining the most critical links in large-scale networks. In addition, a new vulnerability index is introduced to examine properly the consequences of a link closure. The effects of demand uncertainty and heterogeneous travellers’ risk-taking behaviour are explicitly considered. Numerical results for two different road networks show that in practice the proposed approach is more efficient than traditional full scan approach for identifying the same set of critical links. Numerical results also demonstrate that both stochastic demand and travellers’ risk-taking behaviour have significant impacts on network vulnerability analysis, especially under high network congestion and large demand variations. Ignoring their impacts can underestimate the consequences of link closures and misidentify the most critical links.     

Analysing Demand for Suburban Trips: A Mixed RP/SP Model with Latent Variables and Interaction Effects

We analyse mode choice behaviour for suburban trips in the Grand Canary island using mixed revealed preference (RP)/stated preference (SP) information. The SP choice experiment allowed for interactions among the main policy variables: travel cost, travel time and frequency, and also to test the influence of latent variables such as comfort. It also led to discuss additional requirements on the size and sign of the estimated model parameters, to assess model quality when interactions are present. The RP survey produced data on actual trip behaviour and was used to adapt the SP choice experiment. During the specification searches we detected the presence of income effect and were able to derive willingness-to-pay measures, such as the subjective value of time, which varied among individuals. We also studied the systematic heterogeneity in individual tastes through the specification of models allowing for interactions between level-of-service and socio-economic variables. We concluded examining the sensitivity of travellers’ behaviour to various policy scenarios. In particular, it seems that contrary to political opinion, in a crowded island policies penalising the use of the private car seem to have a far greater impact in terms of bus patronage than policies implying direct improvements to the public transport service.     

A review on travel behaviour modelling in dynamic traffic simulation models for evacuations

Dynamic traffic simulation models are frequently used to support decisions when planning an evacuation. This contribution reviews the different (mathematical) model formulations underlying these traffic simulation models used in evacuation studies and the behavioural assumptions that are made. The appropriateness of these behavioural assumptions is elaborated on in light of the current consensus on evacuation travel behaviour, based on the view from the social sciences as well as empirical studies on evacuation behaviour. The focus lies on how travellers’ decisions are predicted through simulation regarding the choice to evacuate, departure time choice, destination choice, and route choice. For the evacuation participation and departure time choice we argue in favour of the simultaneous approach to dynamic evacuation demand prediction using the repeated binary logit model. For the destination choice we show how further research is needed to generalize the current preliminary findings on the location-type specific destination choice models. For the evacuation route choice we argue in favour of hybrid route choice models that enable both following instructed routes and en-route switches. Within each of these discussions, we point at current limitations and make corresponding suggestions on promising future research directions.     

Applying behavioural theories to studying the influence of climate change on young people’s future travel intentions

Transport policy in the UK is seeking to promote the development of low carbon transport technology and to encourage people to choose to use low carbon travel options. This paper draws on existing behavioural theories to study young people’s travel behaviour intentions and the influence on these from their knowledge of, and willingness to act on, climate change. The study involved a series of focus groups with young people aged 11-18 years, where attitudes to transport modes, attitudes towards climate change and travel behaviour intentions were discussed. Knowledge and values are established as the key determinants of young people’s attitudes and behaviour intentions towards transport in the context of climate change. More specifically it is established that young people’s values emphasise speed and freedom and that it is important to young people that the mode of transport they choose is reflective of the image they want to portray.     

Understanding suburban travel demand: Flexible modelling with revealed and stated choice data

We analyse the choice of mode in suburban corridors using nested logit specifications with revealed and stated preference data. The latter were obtained from a choice experiment between car and bus, which allowed for interactions among the main policy variables: travel cost, travel time and frequency. The experiment also included parking cost and comfort attributes. The attribute levels in the experiment were adapted to travellers’ experience using their revealed preference information. Different model specifications were tested accounting for the presence of income effect, systematic taste variation, and incorporating the effect of latent variables. We also derived willingness-to-pay measures, such as the subjective value of time, that vary among individuals as well as elasticity values. Finally, we analysed the demand response to various policy scenarios that favour public transport use by considering improvements in level-of-service, fare reductions and/or increases in parking costs. In general, demand was shown to be more sensitive to policies that penalise the private car than those improving public transport.     

The social context of informal commuting: Slugs, strangers and structuration

Despite considerable interest in the role of social interactions and social context on transportation, there have been very few attempts to explore specific cases of social interaction influencing transportation systems. This paper explores the social practice of slugging, an informal system of carpooling in the Washington, DC area. Slugging emerged in response to the establishment of Virginia’s High Occupancy Vehicle (HOV) lanes in the early 1970s, as single drivers picked up riders alongside the road (slugs) in order to meet the requirements for driving in the less congested HOV lanes. Drawing on the work of sociologist Anthony Giddens, as well as the sociological insights of Georg Simmel and Stanley Milgram, we suggest that the practice of slugging highlights the processes of institutionalization and structuration. This paper details how the region’s mass transportation policies and urban culture have combined to result in an institutionalized practice with particular norms and logics of behavior. We conclude that looking at specific cases where social context has affected transportation, like slugging, could provide useful insights on the impact of social context on transportation policies and systems.     

Activity settings and travel behaviour: A social contact perspective

Using time-use data from Canada, Norway, and Sweden, this study briefly outlines the essence of the activity setting approach and illustrates one aspect of its usefulness by exploring the impact of social contact on travel behaviour. The activity system approach views behaviour in context. Activity settings are generic components of the activity system and studying them using time-use diaries can provide major insights into travel behaviour. Focusing on social contact, this paper characterizes the social environment in terms of social circle (interaction partners) and social space (location). The analysis shows that there are clear differences in the levels of social interaction across various groups, including those who work at home. The 1992 Canadian data showed people working at the workplace spend relatively more time with others, about 50% of total time awake. Working at home reduced the time with others to a low of 15.7%. when people worked at home the family benefited, almost doubling the time spent with them compared to those working at the workplace. Persons working at home only spend the most time alone. There is a tendency for persons with low social interaction to travel more. It is argued that individual need, or want, social contact and if they cannot find it at the workplace they will seek it elsewhere thus generating travel. Whether this is the result of need or opportunity is of minor relevance, what it does suggest is that working in isolation at home will not necessarily diminish travel but rather may simply change its purpose. This revised version was published online in June 2006 with corrections to the Cover Date.     

Modelling contact mode and frequency of interactions with social network members using the multiple discrete–continuous extreme value model

Communication patterns are an integral component of activity patterns and the travel induced by these activities. The present study aims to understand the determinants of the communication patterns (by the modes face-to-face, phone, e-mail and SMS) between people and their social network members. The aim is for this to eventually provide further insights into travel behaviour for social and leisure purposes. A social network perspective brings value to the study and modelling of activity patterns since leisure activities are influenced not only by traditional trip measures such as time and cost but also motivated extensively by the people involved in the activity. By using a multiple discrete-continuous extreme value model (Bhat, 2005), we can investigate the means of communication chosen to interact with a given social network member (multiple discrete choices) and the frequency of interaction by each mode (treated as continuous) at the same time. The model also allows us to investigate satiation effects for different modes of communication. Our findings show that in spite of people having increasingly geographically widespread networks and more diverse communication technologies, a strong underlying preference for face-to-face contact remains. In contrast with some of the existing work, we show that travel-related variables at the ego level are less important than specific social determinants which can be considered while making use of social network data.     

Modelling the impact of alternative transport strategies upon social groups

In this paper, the application of a model representing the impact of interaction between transport costs and the location of housing, population, job employment, shopping and land is described. Two particular uses of the model are considered. Firstly, the effects of changing transport costs upon people of different social status in terms of money and time spent on travelling are examined and compared with results based upon the assumption that the location of population and employment are not responsive to changes in transport cost, as in the conventional transport demand model. Secondly, the effects of six land use‐transport policy sets are examined in terms of the impact upon urban morphology, and the opportunities and travel behaviour of the three social groups. The effects are also compared with the objectives of the strategies.     

Communicating something confidential while travelling by train: the use of a telephone conversation versus silent modes

Wireless ICTs are often used in public transport. Using survey data collected amongst 98 train travellers this article aims to gain insight into important factors that affect train travellers’ intentions to communicate with distant others while travelling. More specifically, the focus is on the decision-making process that leads to the intention to choose for a confidential conversation either via ‘audible’ mobile phone or via ‘silent’ SMS/e-mail. An approach that is related to the Extended Model of Goal-directed Behaviour (EMGB) is applied. Structural equation modelling results indicate that in particular past SMS behaviour, the desire to communicate (goal desire), the perceived efficacy and controllability influence the intention to conduct a confidential phone conversation in the train. The influence of the social environment (e.g. eavesdropping) seems to be less important. Several EMGB constructs are strongly influenced by age. It seems that older respondents have more negative attitudes towards telephoning while travelling by train, and find it more difficult to call other people in such a situation. Finally, they have a lower intention than younger respondents to conduct a confidential conversation over the phone while travelling.

Catching the tail: Empirical identification of the distribution of the value of travel time

Recent methodological advances in discrete choice analysis in combination with certain stated choice experiments have allowed researchers to check empirically the identification of the distribution of latent variables such as the value of travel time (VTT). Lack of identification is likely to be common and the consequences are severe. E.g., the Danish value of time study found the 15% right tail of the VTT distribution to be unidentified, making it impossible to estimate the mean VTT without resorting to strong assumptions with equally strong impact on the resulting estimate. This paper analyses data generated from a similar choice experiment undertaken in Sweden during 2007-2008 in which the range of trade-off values between time and money was significantly increased relative to the Danish experiment. The results show that this change allowed empirical identification of effectively the entire VTT distribution. In addition to informing the design of future choice experiments, the results are also of interest as a validity test of the stated choice methodology. Failure in identifying the right tail of the VTT would have made it difficult to maintain that respondents’ behaviour is consistent with utility maximisation in the sense intended by the experimenter.     

Dynamic stochastic transit assignment with explicit seat allocation model

This paper proposes a stochastic dynamic transit assignment model with an explicit seat allocation process. The model is applicable to a general transit network. A seat allocation model is proposed to estimate the probability of a passenger waiting at a station or on-board to get a seat. The explicit seating model allows a better differentiation of in-vehicle discomfort experienced by sitting and standing passengers. The paper proposes simulation procedures for calculating the sitting probability of each type of passengers. A heuristic solution algorithm for finding an equilibrium solution of the proposed model is developed and tested. The numerical tests show significant influences of the seat allocation model on equilibrium departure time and route choices of passengers. The proposed model is also applied to evaluate the effects of an advanced public transport information system (APTIS) on travellers’ decision-making.     

Scientific research about climate change mitigation in transport: A critical review

This paper seeks to develop a deeper understanding of the research on climate change mitigation in transport. We suggest that work to date has focused on the effects of improvements in transport technologies, changes in the price of transport, physical infrastructure provision, behavioural change and alternative institutional arrangements for governing transport systems. In terms of research methodologies, positivist and quantitative analysis prevails, although there are signs of experimentation with non-positivist epistemologies and participatory methods. These particular engagements with climate change mitigation reflect mutually reinforcing tendencies within and beyond the academic transport community. We first draw on a revised version of Thomas Kuhn’s philosophy of science to explore the path dependencies within transport studies, which are at least partly responsible for the predisposition towards quantitative modelling and technology, pricing and infrastructure oriented interventions in transport systems. We then employ the governmentality perspective to examine how transport academics’ engagements with climate change mitigation depend on and align with more general understandings of climate change in UK society and beyond. The analysis makes clear that ecological modernisation and neo-liberal governmentality more generally provide the context for the current focus on and belief in technological, behaviour change, and especially market-based mitigation strategies. While current research trajectories are important and insightful, we believe that a deeper engagement with theoretical insights from the social sciences will produce richer understandings of transport mitigation in transport and briefly outline some of the contributions thinking on socio-technical transitions and practice theories can make.     

Incorporating social interaction into hybrid choice models

The aim of this paper is to develop a methodological framework for the incorporation of social interaction effects into choice models. The developed method provides insights for modeling the effect of social interaction on the formation of psychological factors (latent variables) and on the decision-making process. The assumption is based on the fact that the way the decision maker anticipates and processes the information regarding the behavior and the choices exhibited in her/his social environment, affects her/his attitudes and perceptions, which in turn affect her/his choices. The proposed method integrates choice models with decision makers’ psychological factors and latent social interaction. The model structure is simultaneously estimated providing an improvement over sequential methods as it provides consistent and efficient estimates of the parameters. The methodology is tested within the context of a household aiming to identify the social interaction effects between teenagers and their parents regarding walking-loving behavior and then the effect of this on mode to school choice behavior. The sample consists of 9,714 participants aged from 12 to 18 years old, representing 21 % of the adolescent population of Cyprus. The findings from the case study indicate that if the teenagers anticipate that their parents are walking lovers, then this increases the probability of teenagers to be walking-lovers too and in turn to choose walking to school. Generally, the findings from the application result in: (a) improvements in the explanatory power of choice models, (b) latent variables that are statistically significant, and (c) a real-world behavioral representation that includes the social interaction effect.     

“I can do perfectly well without a car!”

This article presents the results of a study exploring travellers’ preferences for middle-distance travel using Q-methodology. Respondents rank-ordered 42 opinion statements regarding travel choice and motivations for travel in general and for car and public transport as alternative travel modes. By-person factor analysis revealed four distinct preference segments for middle-distance travel: (1) choice travellers with a preference for public transport, (2) deliberate-choice travellers, (3) choice travellers with car as dominant alternative, and (4) car-dependent travellers. These preference segments differ in terms of the levels of involvement and cognitive effort in travel decision making, the travel consideration-set and underlying motivations. The study showed that for most people there is more to travel than getting from point A to point B, and that there is considerable heterogeneity in middle-distance travel preferences. Policy implications for reducing the need for travel and promoting a modal shift from car to other travel modes are discussed.     

The acquisition of pre-trip information: A stated preference approach

This paper describes a study into the effects of pre-trip information on travel behaviour, carried out as part of the DRIVE project EURONETT. The aim of the study was to investigate travellers' requirements for different types of travel information and methods of enquiry and to relate the process of information acquisition to changes in travel behaviour. The study was carried out using a stated preference approach, built on the use of a microcomputer based simulation of an in-home pre-trip information system offering information on travel times from home to City Centre, by bus and car, at different times of the day. A novel feature of the stated preference exercise was that respondents effectively generated their own choice set of alternatives through the process of information acquisition. Surveys were undertaken in parallel in Birmingham and Athens, thus allowing a comparison to be made between behaviour in typical Southern and Northern European settings.The first part of the paper discusses some of the fundamental behavioural and modelling issues raised by the introduction of advanced traveller information systems. It then describes the study methodology and the stated preference experiment. Results are presented from an analysis of the information acquisition process itself and from choice models relating the acquired information to effects on different dimensions of travel behaviour.     

Social influences on household location, mobility and activity choice in integrated micro-simulation models

Agent-based approaches to simulating long-term location and mobility decisions and short-term activity and travel decisions of households and individuals are receiving increasing attention in land-use and transportation interaction (LUTI) models to predict land-use changes and travel behaviour in mutual interaction. Social interactions between households and between individuals potentially have an influence on a wide range of the long-term and short-term choices involved in these systems. In this paper we identify the areas in which social interactions play a role and address the question how these influences can be modelled in the context of agent-based LUTI models. We distinguish impacts on activity participation (joint activity participation, support-and-help activities) and impacts on decision making (information exchange, social adaptation of preferences and aspirations) as the two main areas of social influence. A prototype of a LUTI model is proposed that accounts for impacts of the social network on longer-term mobility decision making through information exchange and social adaptation of preferences and aspirations. The model is demonstrated in a numerical simulation.     

Towards a microeconomic framework for modelling the joint choice of activity–travel behaviour and ICT use

The rapid development of information and communication technologies (ICT) has been argued to affect time use patterns in a variety of ways, with consequent impacts on travel behaviour. While there exists a significant body of empirical studies documenting these effects, theoretical developments have lagged this empirical work and in particular, microeconomic time allocation models have not to date been fully extended to accommodate the implications of an increasingly digitised society. To address this gap, we present a modelling framework, grounded in time allocation theories and the goods–leisure framework, for joint modelling of the choice of mode of activity (physical versus tele-activity), travel mode and route, and ICT bundle. By providing the expression for a conditional indirect utility function, we use hypothetical scenarios to demonstrate how our framework can conceptualise various activity–travel decision situations. In our scenarios we assume a variety of situations such as the implications of severe weather, the introduction of autonomous vehicles, and the interaction between multiple decision makers. Moreover, our approach lays the microeconomic foundations for deriving subjective values of ICT qualities such as broadband speed or connection reliability. Finally, we also demonstrate the means by which our framework could be linked to various data collection protocols (stated preference exercises, diaries of social interactions, laboratory experiments) and modelling approaches (discrete choice modelling, hazard-based duration models).