| Project/Area Number |
13450209
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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 | Nagoya University |
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Principal Investigator |
MORIKAWA Takayuki Grad.School of Environmental Studies, Nagoya Univ., Professor, 環境学研究科, 教授 (30166392)
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| Co-Investigator(Kenkyū-buntansha) |
KAWAKAMI Shogo School of Eng., Kansai Univ., Professor, 工学部, 教授 (60023058)
KURAUCHI Shinya Grad.School of Eng., Nagoya Univ., Research Assoc., 工学研究科, 助手 (90314038)
YAMAMOTO Toshiyuki Grad.School of Eng., Nagoya Univ., Assoc.Professor, 工学研究科, 助教授 (80273465)
INOKUCHI Hiroaki School of Eng., Kansai Univ., Research Assoc., 工学部, 助手 (10340655)
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| Project Period (FY) |
2001 – 2002
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| Project Status |
Completed (Fiscal Year 2002)
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| Budget Amount *help |
¥6,200,000 (Direct Cost: ¥6,200,000)
Fiscal Year 2002: ¥2,700,000 (Direct Cost: ¥2,700,000)
Fiscal Year 2001: ¥3,500,000 (Direct Cost: ¥3,500,000)
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| Keywords | Advanced Traveler Information System / Travel Behavior Analysis / Route Choice Behavior / Equilibrium Traffic Assignment / Imperfect Information / Latent Class Model / Intelligent Transport Systems / Probe-Car Data / 経路選択 / 情報の不完全性 |
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| Research Abstract |
The aim of this research is to propose the methodologies to quantitatively evaluate the impacts of advanced traveler information systems based on the concept of "bounded rationality" which relax some of the assumptions of "instrumental rationality" postulated in conventional models. Firstly, we developed the two discrete choice models which explicitly consider the mechanism of information searches and processing: one is about the information acquisition, and the other is about the information processing. Latent class models were utilized to represent the heterogeneity of the decision making processes among individuals. These models were empirically applied, and the results showed that the proposed model was superior in both reproducibility and predictive accuracy compared to the conventional models in which "instrumental rationality" is assumed. Also verified was that since the degree of freedom of proposed models are extremely high, it is essential to collect and utilize the various d
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ata sources, such as psychological data and SP data, together with the actual choice data to get the unbiased and effective parameter estimates.
Secondly, we investigated the impacts of advanced traveler information system on transportation network demand. The multi-class user equilibrium model, in which the cognitive levels on travel time and network configuration differ between each class, was developed and empirically applied to the road network of Nagoya metropolitan area. The result showed that we obtained the best fit to the observed traffic flows when we set 20-30% of drivers, mainly private trip drivers, choose only arterial roads. This causes unnecessary congestion on arterial roads. By providing information of the full network to make the equilibrium state, about 70,900 JPY (600 USD) of travel time reduction benefits accrues to such drivers. But we cannot conclude that this concentration to arterial roads is attributed to imperfect information on network configuration or simply due to the preference bias to arterials.
Thirdly, probe car data are analyzed both to directly observe route choice behavior using a large scale probe-car experiment conducted in Nagoya metropolitan area. We investigated a heavily traveled O-D pair for which a toll route and several free routes can be used. It was found that 30-70% travelers used the toll route, implying that VOT distributes. We observed that multiple free routes were used among which travel times differed 10-20%. Also observed was that the toll route was often slower but many drivers chose it. Thus, substantial number of drivers made seemingly irrational decision making. Those observations may partly be explained by imperfect information and other factors than travel time and cost. We also investigated the characteristics of probe car data and its potentials toward the transportation planning, and the results showed that probe-car data could be much richer both in quantity and quality compared to traditional questionnaire type travel surveys. Less
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