Article ID: | iaor200948250 |
Country: | Netherlands |
Volume: | 36 |
Issue: | 1 |
Start Page Number: | 97 |
End Page Number: | 112 |
Publication Date: | Jan 2009 |
Journal: | Transportation |
Authors: | Arslan Turan |
Keywords: | analytic hierarchy process, artificial intelligence: decision support |
Having an effective public participation in transportation planning and project development processes has been a major concern for developed countries. In the United States, for instance, all state Departments of Transportation are subject to the Transportation Equity Act (TEA–21) that formally requires public involvement in transportation planning. Since transportation planning involves public resources and values, judgments by the public should play a key role in determining final decisions. Therefore, all these agencies are required not only to disseminate information to the public, but also to solicit and consider public opinion in forming transportation policy. This work presents a decision support model, with public involvement and public oversight, to help policy makers select appropriate transportation projects for implementation. Since focus groups will face multiple objectives and inexact information in the process, a hybrid model of fuzzy logic and analytical hierarchy process (AHP) is proposed. A set of ‘if–then’ rules based on Weber's psycho–physical law of 1834 is presented to reason from fuzzy numbers to capture essential subjective preferences, pairwise, among the alternatives. The AHP is then incorporated to estimate preference allotments among alternatives. An example application of the suggested method is provided seeking public approval of an appropriate public bus transportation system choosing between one run by municipal authorities and one run by private agencies to show how this procedure works.