|Budget Amount *help
¥4,000,000 (Direct Cost: ¥4,000,000)
Fiscal Year 2002: ¥1,900,000 (Direct Cost: ¥1,900,000)
Fiscal Year 2001: ¥2,100,000 (Direct Cost: ¥2,100,000)
In this study, we propose a normative mathematical model with which we forecast multiple route choice behavior equilibrium flow pattern with endogenous demand of ATIS (Advanced Transportation Information System) users. This model is basically based on the multiple user network equilibrium model provided by Yang (1998), but we can formulate the other equivalent optimization-programming problem using an alternative and appropriate definition on ATIS users demand modeling. By using this model, we can measure the social benefit that is consistent with the demand-modeling framework. Furthermore, we obtain a very interesting paradox that the ATIS information might not always produce social efficiency to the transportation. Furthermore, we find the useful results that total cost of the system is sometimes lower in the case when the ATIS information cost is charged to drivers than in the case when the ATIS information cost is free of charge.
On the other hand, this study proposed the introducto
ry effect of advanced traveler information systems using two methods, WTP and [MSUE/ATIS] model. First, we performed the citizen perception survey to the introductory effect of VICS-unit. We evaluated the value of ATIS by WTP survey, and estimated the benefit. Furthermore, the unknown parameter of [MSUE/ATIS] model was estimated using WTP model. Finally, [MSUE/ATIS] model was applied to Kumamoto Urban Area and Seien Urban Area in order to estimate the benefit. We found that the introductory of ATIS in the area, where traffic congestion is heavy and travel cost is large, is effective.
Finally, this paper proposes a method of inverse-estimating the unknown parameters of the composition model, which composed of integrated network equilibrium model using observed traffic. A bi-level optimization problem is built in order to apply the method to the [MUSE/VICS-Demand] model. It is proved that the proposed method can be used by means of numerical simulations using a model network. Moreover, it is also proved that a bi-level optimization problem can be efficiently calculated by nonlinear sensitivity analysis. The following results about the estimation of the unknown parameters are found: (1) there is an effective setting method for a set of observed links; (2) it is possible to improve precision of estimate by making the observation error small. Less