This thesis develops econometric models of departure time and travel mode choice to evaluate dynamic transportation policies. Dynamic policies affect travel attributes differently throughout the day. Both departure time and mode choice are modelled with Random Utility Maximizing (RUM) Generalized Extreme Value (GEV) discrete choice models that capture systematic and random heterogeneity. Departure time is represented by a heteroskedastic generalized extreme value model (Het-GEV) with overlapping choice sets. Studying the Greater Toronto and Hamilton Area (GTHA), models are estimated using Revealed Preference (RP) household travel data from the 2006 Transportation Tomorrow Survey (TTS). Empirical models are used to evaluate dynamic transit and road pricing policies. Results indicate that the models are capable of capturing mode and time switching behaviour in response to peak pricing policies. To alleviate demand while maintaining transit mode share, a road charge and a moderate, flat, transit fare increase throughout the morning peak are recommended.

This thesis develops econometric models of departure time and travel mode choice to evaluate dynamic transportation policies. Dynamic policies affect travel attributes differently throughout the day. Both departure time and mode choice are modelled with Random Utility Maximizing (RUM) Generalized Extreme Value (GEV) discrete choice models that capture systematic and random heterogeneity. Departure time is represented by a heteroskedastic generalized extreme value model (Het-GEV) with overlapping choice sets. Studying the Greater Toronto and Hamilton Area (GTHA), models are estimated using Revealed Preference (RP) household travel data from the 2006 Transportation Tomorrow Survey (TTS). Empirical models are used to evaluate dynamic transit and road pricing policies. Results indicate that the models are capable of capturing mode and time switching behaviour in response to peak pricing policies. To alleviate demand while maintaining transit mode share, a road charge and a moderate, flat, transit fare increase throughout the morning peak are recommended.

No description available.

This thesis proposes a framework that combines a mode choice model with a large scaled agent-based multimodal traffic microsimulation. Both components are discussed with respect to their development as separate entities. The mode choice model uses a formulation that explicitly considers latent modal captivity despite using conventional travel survey data. An existing multimodal microsimulation traffic assignment model used in the study area is enhanced and partially calibrated for use with the MATSIM traffic assignment tool. Both of the components are then tested independently in terms of statistical and behavioral validity and a conceptual procedure to test the implications of the mode choice model on mode switching behaviour within the traffic assignment model is presented. Other applications of both the travel assignment model and mode choice model are discussed. In order for the framework to become operational, further development with respect to the traffic assignment model is required.

This thesis proposes a framework that combines a mode choice model with a large scaled agent-based multimodal traffic microsimulation. Both components are discussed with respect to their development as separate entities. The mode choice model uses a formulation that explicitly considers latent modal captivity despite using conventional travel survey data. An existing multimodal microsimulation traffic assignment model used in the study area is enhanced and partially calibrated for use with the MATSIM traffic assignment tool. Both of the components are then tested independently in terms of statistical and behavioral validity and a conceptual procedure to test the implications of the mode choice model on mode switching behaviour within the traffic assignment model is presented. Other applications of both the travel assignment model and mode choice model are discussed. In order for the framework to become operational, further development with respect to the traffic assignment model is required.

The Chinese outbound tourism market has experienced rapid growth over the past few years. This noticeable development provides the background and rationale for the study that identifies the travel behaviour of Chinese tourists, and the expectation and perception regarding South Africa. Based on the findings, some recommendations for marketing strategies and implementation are given, in addition to suggestions for future research directions in this field. The theoretical discussion focuses on concepts of travel behaviour. Travel behaviour, including travel motivation, decision-making process, and destination choice are then presented in more detail. The development of the Chinese economy and Chinese outbound tourism are also presented and discussed. The empirical research focuses on the travel behaviour of Chinese outbound tourists. The goal here is to determine and analyse the travel behaviour of tourists, outbound from Beijing, and their views on South Africa as a tourism destination. To accomplish this, the empirical research is designed from the quantitative perspective, and the data was collected by fieldworkers at the Beijing International Airport, using intercept surveys. This helps the researcher to understand the needs, motivation, and behaviour of the Chinese outbound tourists and assists the researcher in analysing the marketing strategy of South Africa as a tourist destination. / Thesis (M.Com. (Tourism))--North-West University, Potchefstroom Campus, 2008.

The increasing scale of, and demand for, civil air transport has necessitated ever greater numbers of passengers and staff travelling to and from airports. At airports worldwide, private vehicles represent the vast majority of these surface access journeys and this has led to severe problems of traffic congestion and raised levels of air pollution. Consequently, UK and international airports are re-evaluating their approach to surface access mode choice and considering how to reduce the reliance on private vehicles. Despite improvements in public transport links at some airports, in the UK it is currently estimated that around 65% of surface access trips at large airports are undertaken in private cars, with this figure being as high as 99% at smaller regional or secondary airports. The problems associated with high private vehicle use are likely to become even more acute in the future given the forecasted growth in demand for UK air travel. Surface access is a complex airport management issue as decision makers must balance the often competing requirements and demands of different user groups with the wider commercial and environmental goals of the airport. Passengers pose a particular problem due to the large number of trips generated, and the wide range of factors affecting their travel. Passengers are also important because they represent the airport s primary customers. The aim of the thesis is to examine passenger surface access travel behaviour in order to make recommendations for reducing private vehicle use. The research adopts a social psychological approach, employing two theories of attitude-behaviour relations, the Norm-Activation Theory and the Theory of Planned Behaviour, in order to identify groups of passengers with the potential to reduce their private vehicle use. Research methods employed to fulfil the aim include interviews with surface access managers at UK airports and a questionnaire survey of passengers at Manchester Airport, an international airport in the North-West of England. It is found that passenger mode choice decisions are motivated primarily by considerations of self-interest, as posited in the Theory of Planned Behaviour, rather than normative or moral elements, as proposed by the Norm-Activation Theory. As well as attitudes, passengers are also found to vary considerably in terms of their specific personal, situational and spatial characteristics. For example, passengers using public transport are likely to be travelling alone from areas further from the airport and flying without checked-in luggage. Using this combined attitudinal, situational and spatial information, eight distinct passenger groups are then identified. Two of these groups, described as the Public Transport Advocates and the Pessimistic Lift Seekers, are found to have the greatest potential to reduce their private vehicle use. Overall, it is important that strategies targeted at reducing private vehicle use and encouraging public transport use address both the physical and perceived barriers preventing behavioural change. Furthermore, while airport managers tend to favour implementing so called soft incentive measures for encouraging modal shift as opposed to more draconian measures, in the future it is likely that decision makers will increasingly need to find ways of implementing the latter in a fashion that is both effective and acceptable to airport users.

The overall goal of this research is to measure drivers' attitudes towards uncertain and unreliable routes. The route choice modeling is done within the discrete choice modeling framework and involved use of stated preference data. The first set of analysis elicits travelers' attitudes towards unreliable routes. The results of the analysis provide useful information in relation to how commuters value the occurrence/chances of experiencing delay days on their routes. The frequency of days with unexpected delays also measures the travel time reliability in a way that is easy to understand by day-to-day commuters. As such, behaviorally more realistic values are obtained from this analysis in order to capture travelers' attitudes towards reliability. Then, we model attitudes toward travel time uncertainty using non-expected utility theories within the random utility framework. Unlike previous studies that only include risk attitudes, we incorporate attitudes toward ambiguity too, where drivers are assumed to have imperfect knowledge of travel times. To this end, we formulated non-linear logit models capable of embedding probability weighting, and risk/ambiguity attitudes. A more realistic willingness to pay structure is then derived which takes into account travel time uncertainty and behavioral attitudes. Finally, we present a conceptual framework to use a descriptive utility theory, i.e. cumulative prospect theory in forecasting the demand for a variable tolled lane. We have highlighted the issues that arise when a prescriptive model of behavior is applied to forecast demand for a tolled lane.

Thesis (M.Com. (Tourism))--North-West University, Potchefstroom Campus, 2008.

Conventional transportation demand management approaches have had limited success in reducing automobile dependency. As a result, it has become increasingly important to understand the decision-making processes involved in determining travel behaviour. The purpose of this dissertation is to extend research on urban form and travel behaviour beyond adult travel by examining teen travelers aged 13-19 in the Greater Toronto Area. Data from the Transportation Tomorrow Survey (TTS) survey are used to study four main research questions: 1) How has teen mode choice changed from 1986 to 2006? 2) How do these choices vary as teens transition from the 13-15 age group to being of driving age (16-19)? 3) How do these choices vary across the different urban and suburban regions of the GTA? 4) What are some of the differences between teen travel and adult travel? The issue is further probed through the collection of quantitative and qualitative travel data from first year students at the University of Toronto, and a series of focus groups held in locations in the GTA. The first year survey explores attitudes towards different modes in relation to the locational attributes of the respondent‘s hometown neighbourhood. The focus group sessions involve interviews with 26 teen and a take-home parental questionnaire. Results show that across the GTA, active transportation has decreased while auto passenger mode shares have increased. Younger teens walk more and older teens take transit more for both school and discretionary travel. Jurisdictions with better transit supply and orientation have higher transit mode shares for school trips, but discretionary trips have low transit mode shares. Walk mode shares for both school and discretionary travel are similar across all jurisdictions, regardless of whether they are urban or suburban. Additionally, the survey participants' narratives illustrate that the desire to travel actively and independently is strong. However, the reality of the final travel choice is determined by the presence of supportive infrastructure that facilitates active mode choices while shaping perceptions and attitudes formed as a result of daily travel experiences. Findings illustrate the relevance of qualitative work in advancing transportation research--particularly in understanding human travel decisions.