1.1 Motivations and background
Transportation plays an important role as a key chain of the social systems and ecosystems. Sustainable transport has drawn increasing worldwide attentions under the policies and initiatives of sustainable development provoked by the Brundtland Commission, formally the World Commission on Environment and Development (WCED) since 1987. The OECD (1996) defined environmentally sustainable transport as transportation that does not endanger public health or ecosystems and meets mobility needs consistent with use of renewable resources at below their rates of regeneration and use of non-renewable resources at below the rates of development of renewable substitutes. Pertaining to this concept, a number of earlier works attempted to address what the scope of transportation sustainability meant and what the directions and indicators of sustainable transportation were. For example, Black (1996) defined sustainable transport as “…satisfying current transport and mobility needs without compromising the ability of future generations to meet these needs.” Whatever it is defined, most researchers have agreed that sustainable transport development is highly affected by such factors as spatial and land-use planning, government policy, economic forces, technology, and social and behavioral trends.
Towards transportation sustainability, it is essential to guide people to choose low- or zero-emission and energy conservation mode. However, people always choose the most economical and convenient mode depending upon their life styles. Use of private vehicles without paying the external pollution and congestion costs seems a popular
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choice worldwide, which also explains the rapid growth in the ownership and usage of cars and motorcycles. The greater usage of private vehicles will inevitably lead to a serious environmental disaster.
To control the usage of private vehicles and to encourage public transportation patronage is a classical “Carrot-and-Stick” policy to relieve such an environmental disaster. However, in most of demographic countries, the Stick-related policies are usually not appealing. Therefore, under government budget and ecological footprint constraints, how to provide adequate favorable incentives to encourage the ridership of public transportation deserve in-depth studies.
However, mode choice behaviors are significantly affected by level of service and travel cost of transport modes; while the level of service and travel cost determines the mode choices inversely. In addition, many stakeholders, such as passengers, transit operators, government, are involved during the decision process. The complexity of transport systems not only derives from the pluralism of infrastructures and vehicles, it also sources from the behaviors of people and organizations. Very few studies have employed quantitative methods that can satisfactorily elucidate the interactions among different transport systems under sustainability contexts, perhaps due to the complex nature of transport systems. Without an analytical framework or robust modeling, quantitative results of insightful directions and interactions among different sectors are barely obtained. Therefore, to propose policy towards transportation sustainability, it is necessary to develop an integrated model which can model such complex interactions among various modes and stakeholders and to clearly indicate the directions of effective policies.
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In addition, “ecological footprint” is one of tools to measure what natural burdens and how sustainable an activity is, which is defined as the total area of productive land and water area required to provide support for that activity (Wackernagel and Rees, 1996). This tool is helpful to unify different units of resources used and environment burdened during the transportation process and to compare with the amount of natural resource which we enjoy.
1.2 Research objectivities
Based on the abovementioned motivations, the aims of this study are：
1. To review and summarize the studies related to “sustainable transportation”,
“ecological footprint”, and “quality of life” to serve as the step stone of this study.
2. To develop a bi-level programming model to determine the optimal strategies for subsidizing public transportation toward Quality of Life maximization and Ecological Footprint minimization under the government budget constraint and lower-level model (user equilibrium model).
3. To validate the proposed model by an exemplified example.
4. To draw conclusions and to recommend the strategies through scenario analysis and sensitivity analysis.
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1.3 Framework and organization
The research flowchart of this study is depicted in Figure 1.1.
Introduction
Literature Review
Model Formulation
Quality of Life Ecological Footprint
Solution Algorithm
Sensitivity Analysis
Scenario Analysis
Suggested Policies
Discussions and Conclusions
Data Collection
*Taipei O-D Matrix
*Ecological Footprint of Each Modes
*Travel Cost of Travelers
*Travel Time of Travelers Bi-level Programming Model
Case Study
Figure 1.1 Research flowchart
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1.4 Research procedure
Following the research objectives and the flowchart in Figure 1.1, the research procedure of this study is designed below：
1. Problem definition
Clearly define the research target and scope of this study and to confirm the objectivities of this study. Determine the potential methodologies and tools related to this research.
2. Literature review
Systematically review the studies related to sustainable transportation, ecological footprint, and quality of life for selecting the key indicators influence sustainability and quality of life.
3. Research framework
Due to the complexity of the transport systems, the proposed model will contain several sub-models. To clearly indicate the relationships among these sub-models, a research framework is developed.
4. Model formulation
The proposed bi-level programming model is formulated as：
I. Upper level：
The decision maker in upper level is government, which aims to determine an optimal strategies for subsidizing public transportation to maximize quality of life and minimize ecological footprint under the budget constraint.
II. Lower level：
There are two models in the lower level： a model choice model (Logit model) and an user equilibrium model. The decision maker in lower level is the users of the transportation system. Users attempt to make mode choice and route choice decisions
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to be better off.
5. Exemplified example
An exemplified example is designed validate the proposed model and to compare the performances of different subsidy strategies.
6. Sensitive analysis
This chapter presents the sensitive analysis of parameters in the proposed model, including changes in budget, mode choice coefficients, and ecological footprint coefficients.
7. Scenario analysis
To further investigate the effect of situation changes, three scenarios： optimistic, neutral, and pessimistic are respectively tested and compared.
8. Conclusion and suggestion
Based on the results of case study, effective strategies towards transportation sustainability are recommended. Suggestions for future studies are also indicated.
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