2007 Fiscal Year Final Research Report Summary
A Study on Evaluation of Traffic Information Considering Interference between Divers under Uncertainty
| Project/Area Number |
17360246
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
交通工学・国土計画
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| Research Institution | Kyoto University |
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Principal Investigator |
KITAMURA Ryuichi Kyoto University, Graduate school of Engheering, Professor (60252467)
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| Co-Investigator(Kenkyū-buntansha) |
YOSHII Toshio Kyoto University, Graduate school of Engineering, Associate Professor (90262120)
KIKUCHI Akira Kyoto University, Graduate school of Engineering, Assistant Professor (00343236)
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| Project Period (FY) |
2005 – 2007
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| Keywords | Uncertainty / Travel Time Perception / Heuristics / Travel Behavior Analysis / Travel Time Information / Participatory Simulation |
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| Research Abstract |
Proposed in this study is a measure of the perception of travel time variability, perceived travel time bandwidth. Results of a six-week diary survey of expressway users in the Osaka metropolitan area of Japan have revealed that perceived bandwidth explains the variation in safety margin more than does the standard deviation of recorded travel times, that the perception of variability is important in explaining travel decision, and that an objective measure of variability, such as the standard deviation of travel times, may not he an effective variable to account fur traveler' decision under uncertainty.
The analyses of experimental data, obtained from 76 subjects, lend support to some of the hypotheses postulated on the perception of representative travel time. It has shown that availability by recentness applies in the perception of representative travel time before habitualization. The results have also shown that the association between perceived representative travel time and experienced travel times weakens after habitualization. Neither availability by extremity nor anchoring has been demonstrated by the analysis of the experimental data.
The numerical examples of this study provide results that improvements in network flow are negligibly small even when precise information on travel time is provided. In case where no predictive travel time information is present, results of agent-based route choice simulation indicate that higher levels of drivers' cognitive capabilities tend to produce more self-organization of drivers and stable network flows. It is also shown that information on routes that a driver did not take is important for this self-orgarnization. Simulation results also indicate that predictive travel time information is ineffective even when it is accurate.
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