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Trans. Planning Journal
| Title | Using Fuzzy Approximate Reasoning Processes in Modeling Commuters’ Decision Behavior: A Case Study |
|---|---|
| Author | Chee-Chong Tong, Tsu-Yu Chao |
| Summary | Probability or stochastic choice models have been widely applied to address the uncertainty of traveler's decision behavior. On the other hand, Zadeh's fuzzy set theory introduced to address the phenomenon of ambiguous events rather than random nature may be suitable for exploring human decision behavior such as travel decisions. This study is an attempt to apply fuzzy reasoning method to study travel behavior with a case of auto-driving commuters’ daily departure time and route choices. Within such framework, driver perceptions of uncertain outcome of attributes affecting their travel choices are due to vagueness rather than randomness. A rule-based reasoning process is therefore applied to model the observed behavior rather than the commonly used utility maximization. Furthermore, a systematic hierarchy approach was implemented to describe commuters’ decision process. Observations were established from a controlled experiment in which real commuters were interacting with a simulated traffic context. Six sequential departure time and route decision models were established based on fuzzy inference concepts and those preliminary observations. Each model was then paired with its respective observations. Excluding those with too few observations, three models were validated and showed promising results with matching ratios (between actual decisions and model outputs) higher than 70%. |
| Vol. | 31 |
| No. | 4 |
| Page | 679 |
| Year | 2002 |
| Month | 12 |
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