Transport evaluation methodology in Korea has remained largely unchanged even though the evolution of the transport planning process has changed in its nature and circumstances. The economic analysis has played an important role as a decision making method, and the Government has the leading role as a single decision maker. As a result, there are so many debates on most of transport investment projects by other interest groups and by the fact that other non-economic attributes are not properly considered in the evaluation process. Therefore, it is necessary to avoid this costly indecision and incomplete evaluation. As a result, the recent work has focused on improving public participation and evaluation methods utilising multiple criteria decision making methods which are able to reflect diverse interests of multiple actors involved in the project, environmental issues, socioeconomic concerns and public discontent in evaluation process, and to respond to the changed nature of transport planning. In this research, the analytic hierarchy approach which enables to combine the advantages in quantifying the tangible factors from CBA and in deriving weights of the factors from the AHP was attempted to evaluate the transport investment project in Korea as the methodology through reviewing and assessing many multiple criteria decision making methods. The case for application was chosen from the real project implemented by Korean government so as to compare the current evaluation method with the analytic hierarchy approach, one of multiple criteria decision making methods. The project is to develop a high speed rail network passing through/by a historic city with many cultural assets, so there are many conflicting debates between transport efficiency and cultural conservation among the stakeholders affected by this project, supplier, user and community. For the application and evaluation of the project, a model with five levels of hierarchical structure with three stakeholders, six objectives, seven elements and three alternatives was developed. A total of 615 respondents from transport experts, government officials and the general public answered the survey questionnaire to find out the degree of importance for each stakeholder's role on this project investment from transport experts, and a relative preference for each attribute as main factor from all stakeholders. With the evaluation process and results (including alternative ranking) from both methods, they were compared with each other. In addition to this, the applicability and suitability of the analytic hierarchy approach method for the evaluation of transport investment project in Korea were assessed by several assessment criteria. The analytic hierarchy approach (through its application) provided much wider scope than the current evaluation method. It showed a systematic framework for the evaluation in which all possible factors should be judged with the distribution of weights on all stakeholders incorporating qualitative and quantitative information. In addition, it showed the applicability of the analytic hierarchy approach to the transport project due to its ability to deal with complex problems with conflicting attributes and to elicit the preferences of many stakeholders affected by the project into the evaluation process. However, it also showed some drawbacks to be overcome such as a large amount of data and information requirement, inherent difficulty in survey implementation, difficulty in structuring a hierarchy, especially in checking the homogeneity.

Stated Preference (SP) methods have been used extensively in transport research and elsewhere both for demand forecasting purposes and to value the importance attached to different product features and travel attributes. Alongside the broader acceptance and wider application of SP methods, some practitioners (Bates, 1998; Ampt et al., 2000; Wardman and Shires, 2001) have argued for greater openness in discussing what they see as significant concerns surrounding SP. The present study is motivated by the desire to analyse and reduce biases in the SP application, specifically addressing the issue of the strategic biasing of SP responses. The review of biases observed in the previous SP applications explored the sources of bias, which can be categorized as unrealistic design, incentive to strategic bias and task complexity effects. Amongst these, the issues of design/scenarios specification and task complexity have received a considerable amount of attention. On the other hand, and despite serious concerns in the early literature, the strategic biasing of responses tends to have been overlooked in recent times, particularly within the SP methodology. This study is motivated by the desire to investigate the incentives for respondents to bias their answer in the SP survey and methods to amend the bias. This study reviewed and summarised concerns surrounding the extent to which the SP responses to hypothetical questions reliably reflect individuals' true preferences when there is an incentive to bias responses. The discussion was illustrated with examples from research in transport field, environment science and marketing. In an empirical demonstration using data obtained from 1222 respondents (10885 preference observations) on the valuation of the improved rolling stock in Greater Manchester, UK, this study presented results for different designs. Based on the review of studies on rolling stock in recent years, a suite of SP experiments were designed to investigate the effects of different designs on responses. Two factors were introduced into the experiment, a `cheap-talk' script and `adding more attributes to mask the research aim', to amend incentives to bias. In the experiment, post-questionnaire questions on respondents' perception of experiments were introduced. More specifically, respondents' perceptions of the task load, familiarity of experiment alternatives together with their perceptions of the attribute change were added to probe the decision making process and the impact of perception on the decision making. Standard logit models were used to demonstrate the overall effects of variables for the whole sample. The segmentation model, based on the incremental factors, was used to identify respondents' taste variations. The heteroskedastic multinomial logit (HMNL) model was used to incorporate the impact of design factors, respondents' characteristics and perceptions into the scale parameter, which were unable to be captured by the standard logit model. This study found that the cheap-talk script decreased the valuation of the improved rolling stock by 20% on average, through increasing respondents' sensitivity to the cost attribute in the SP survey. However, this impact was not significant at the 5% significance level. This indicates that the warning message will help individuals to amend the incentive to strategic bias in the SP experiment; however bias may remain in our study. This study did not detect significant impact of the complex design on the valuation of the improved rolling stock, although task complexity effects were detected where a large error variance was found in the complex SP design. Individuals' perceptions have significant impacts on the valuation and model estimation precision. Individuals' familiarity with alternatives in the experiment increased the value of the improved rolling stock and improved the estimation precision. Individuals' perceptions of potential price increase have an impact on the valuation and estimation precision. The more likely respondents perceived the potential price increase, the fewer preferences were given to the improved rolling stock and respondents were observed to be more consistent in their choice making. In brief, this study suggests that incentives to strategic bias exist in the SP experiment due to its hypothetical nature. Warning message such as a CT script is helpful to amend individuals' incentive to strategic bias. Attention should be made to the complexity of the experiment, as respondents are subjected to certain cognitive ability. In the SP analysis, individuals' perceptions can be incorporated into the model analysis.

Given the severity of the impacts arising from climate change and the short timeframe available regarding mitigation, it is imperative to reduce emissions of greenhouse gases. Road transport is a significant contributor to UK CO2 emissions, with the majority arising from personal road transport. A working model of a Tradable Carbon Permit (TCP) scheme was therefore designed to achieve a 60% reduction of CO2 emissions from personal road transport by 2050. A proportion of the annual carbon budget would be given to individuals as a free carbon permit allocation. Following the consumption of the free carbon permits, an individual must then purchase any permits required in the future from a centralised market. Alternatively, there is an opportunity to sell unused permits. Fuel price increases were recognised as having the potential to achieve an identical emissions target at a much lower cost. Hence, conventional elasticities were used to derive a comparative measure to the TCP scheme. A range of practical considerations regarding both policies were discussed, including approximate costings, social impacts and implementation. An innovative survey design was developed to explore the feasibility of applying a TCP scheme and a system of fuel price increases (FPI) to the personal road transport sector. A series of individual interviews were conducted to gather opinions related to the impacts (including costs and benefits), effectiveness (ability to meet the emissions target), fairness and acceptability of both measures. Bespoke software was used to record behavioural response and display respondents' travel data alongside their free permit allocation and estimated spending at three points in time. A range of qualitative and quantitative results are reported. The findings revealed a stark contrast in opinions and attitudes towards the TCP scheme and FPI, with the TCP scheme being more favourable in every aspect in addition to achieving a much greater level of behavioural response and hence carbon reductions.

The main objective of this research was to improve the understanding of drivers’ behaviour while negotiating traffic calming measures, through the study of the impacts of these measures on speeds. A case study was conducted in the City of York focusing on speed humps (flat-topped and round-topped), speed cushions and chicanes implemented in sequence. Data collection was conducted at three calibration and three validation sites with vehicles’ passing times simultaneously recorded at 16 points along the links. From these data a speed profile for each individual vehicle could be derived. The influence of various combinations of traffic calming measures on speeds of unimpeded cars and vans was evaluated through those speed profiles, and through acceleration profiles deduced from speed profiles. The investigation of the hypotheses established from the analyses of speed and acceleration profiles gave insights into specific issues such as the consistency of crossing speeds, the additive effect of subsequent measures, the acceleration and deceleration rates associated with individual measures and travel times along calmed links. The knowledge acquired from these analyses was applied to the formulation of a speed profile model. To describe drivers’ behaviour along traffic calmed links an empirical model was developed using multiple regression analysis techniques based on data collected at the calibration sites. Speeds along calmed links were described as a function of the input speed, the type of measure and the distance between measures. The speed profile model was shown to be a good representation for the data from the calibration sites. It efficiently predicted speeds of unimpeded vehicles over a given combination of traffic calming measures in sequence. The validation process also indicated that the model provided a good representation of the observed profiles at these sites, with the exception of the prediction of the effects of the chicanes on speeds. This type of measure was shown to produce diverse impacts on speeds which depended on the detailed design. While the model is a useful design tool, recommendations have been made for further enhancement to it.

The relationship between travel growth, increased congestion and effectiveness of traffic management measures can be better understood by examination of change in people’s travel patterns due to congestion and its mitigation policies. The studies suggested that combined models are vital to accurately foresee the impact of policies on travel behaviour, as they integrate the effect of congestion on the scheduling of activities through feedback mechanism. Models within the Activity-based approach predict an individual activity-agenda and its schedule but they lack in representing congestion as an endogenous variable. In contrast, combined models are limited as they tend to incorporate fewer scheduling dimensions for a part of the activity-travel pattern (e.g. home to work trip). Based on this, the primary objective of this thesis is to contribute towards improvements and extensions of the existing combined models. This thesis presented a combined model that integrates the modelling of activity scheduling dimensions (for daily and weekly activity-travel patterns) with the dynamic representation of congestion under the framework of the fixed point problem. Modelled scheduling dimensions include: departure time, activity duration, activity sequence and route choice. The essential aspect of the model is based on the trade-off between the utility of participating in various activities, which contain time-of-day preference and satiation effects, and the disutility of travel. The development process presented for the model is generalised and it can accommodate any operational model within the demand and supply sides. However, the model application in this thesis is limited to the simplified network which can be extended for a real network by following the notions of model development. A variety of numerical experiments were performed in order to assess the model working and the implications of a range of policies. Results obtained from all the numerical experiments are plausible and these are explained well in the thesis.

This study investigates the drivers' route choice in response to variable road user charges and traffic information. Firstly, this study investigates the effects of information concerning traffic conditions on drivers' route choice behaviour and the way in which drivers evaluate the value of information concerning delay time. Secondly, drivers' response to different types of variable road user charges and their sensitivity to these road user charges are explored. Thirdly, the way that the uncertain information influence drivers' behaviours are also analysed. Finally, this study investigates the extent to which socio-economic characteristics influence drivers' responses to road user charge and to the information concerning traffic conditions and charges. The traffic information is provided via VMS and related to the expected delay time. Three types of the variable road user charges are applied: fixed charges; timebased charges; and delay time-based charges. Three SP surveys are conducted to collect data. The main survey is conducted in Leeds and Seoul, and the additional survey is conducted in Leeds. Logit models are used for analysing the main SP survey data. The repeated measurement problem in the main survey data is corrected using the jackknife method and Kocur's method. A regression method is used in the analysis of the additional survey data. Some results reveal that Utility Theory was not enough to explain the results. Therefore, Prospect Theory is applied to the results and is found to give a satisfactory explanation. The results indicate that drivers are less likely to choose a route characterised by recurrent delays and as the length of delay reported on their usual route increases drivers value delay time information more highly than free travel time and become increasingly sensitive to delay time as it increases. The delay thresholds in this study are 10 minute for the normal delay time and 15 minutes for the extra delay time on VMS.

As a new technology, smart card ticketing for public transport has become increasingly popular across the world. Now smart cards and the traditional fare payment methods, cash and paper-based travel cards, have become three major fare payment options in public transport systems. The success of smart card applications across the world led to the realisation of the potential of smart card ticketing by some local governments and public transport service providers in China. For example, in Dalian, China, more than one million public transport smart cards have been issued since the payment application was just introduced in July 2001. However, the traditional payment methods (i. e. cash and travel cards) are still in use in most Chinese cities. Passengers may choose between smart cards and traditional payment methods, according to their perceptions. Therefore, the aim of this research is to identify the fare payment preferences of passengers based on the existing and prospective situations for three fare payment methods (i. e. cash, travel cards and smart cards), to carry out the user demand analysis and provide an insight into the benefits and effectiveness of smart card ticketing. The revealed preference (RP) and stated preference (SP) surveys were designed and carried out in Dalian, China, where the smart card project has been successfully implemented. In the data analysis, two different models are discussed: firstly standard logit models are used to analyse the joint RP and SP data. Secondly, two kinds of new techniques: fuzzy logic (FL) and artificial neural network (ANN) methods are introduced as an alternative to model discrete choice data. The motivation for using FL and ANN is that these two models can be non-linear and simulate human's decision making process without any a priori assumptions between inputs and outputs. The purpose of using FL and ANN in this research is to explore and compare the forecasting ability in the user demand analysis and model performance between new techniques and logit models. Finally, results of the analysis, including forecasted market shares, valuation of attributes, fare elasticities, etc, indicate the increasing trend of smart card use in future development. Through monetary valuations, the importance of attributes is determined, such as multifunction and top-up/purchase options for smart cards. In addition, relevant policies are suggested to authorities to enhance the smart card payment service.

Recent developments in information and communication technology have meant that mobile commerce will have an increasingly important influence on the travel behaviour; in particular on how, when and where people choose to use their time to conduct activities. In the cases of activities involving the use of mobile services, such as m-shopping or m-banking, the conventional strong connection between the utility which one derives from an activity and its timing and duration are weakened or even broken such that existing utility-maximization models are not suitable in these contexts. This thesis presents a novel approach to characterising the utility of activities which can be applied in a broader set of circumstances, especially those such as m-services in which technology relaxes the patio-temporal constraints of activity participation. Building on concepts from both the microeconomic literature and the activity scheduling literature, the thesis proposes a unified utility framework based on an activity production approach, which is characterised by an activity production function. In this approach, an activity is regarded as the archetypal "small firm‟ theorised by Becker (1965). An individual transforms the inputs (purchased market goods, time, and technology) into the outputs (consumption 'commodities) through some activity production process. Both the production process and the outcome of consumption are potential sources of (dis)utility. We show how this framework generalises existing activity utility model and demonstrate how it can be extended to accommodate activities performed in both electronic and mobile contexts. A stated choice exercise was undertaken to obtain the data necessary to estimate utility models based on this new framework. In this exercise, a hypothetical shopping choice scenario was presented to respondents and a D-efficient design was adopted to investigate people‟s decision making with respect to shopping. Using the cleaned data generated by this data collection program, the basic model with the best overall level of fit was identified. Theoretical and empirical implications were discussed. Strong evidences of taste heterogeneity among respondents were also found.

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