This paper presents a model for predicting mixed mode trips within a network equibrium framework, in which for given total origin-destination trips the trips of primal transits, of auxiliary transit as access mode and the users of terminals of those primal transits are simulaneously predicted. Access modes choice, terminal choice of transit and choice of primal transit are structured as the nested logit, being assumed to be competitive with the automobile choice. The model is formulated as a mathematical optimization program of which Kuhn-Tucker conditions provide a generalization of a combined modal split and assignment model. An iterative solution procedure is proposed to solve the mathematical program and its convergency is examined.

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This study aims to develop a combined modal split and assignment model in which users can choose modes and routes simultaneously. The concept of generalized cost is introduced into the model and various time values of, such as, users of car, bus, railway and also walking or waiting time value are used as well in order to get the tradeoff between cost and time exactly. The interaction of private cars and transit vehicles on the road network are considered in some extent.
Most of the effect factors, such as transfer time, waiting time, fare system, feeder function of bus, etc. can be considered in it. The model is verified by applying to Nagoya City. Large networks are set up based on the practical traffic conditions of 1981 and 1991 separately. Parameters and time values are calibrated from survey data. The OD and link traffic correlated coefficients and RMS between survey data and forecasting data are calculated and analyzed. The results show the model possesses high applicability.

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In order to elucidate the phenomenon observed in ballasted track that irregularity of rail level accumulates in terms of the plastic deformation of railroad ballast, vertical and horizontal cyclic loading tests of constant load amplitude were performed with full-scale track. As a result, it was revealed that an effective estimation of the deformation of railroad ballast needs considering coarse granular materials as its material property. Besides, the deformation properties were quantified by test results, and a method to predict deformation quantity of railroad ballast was proposed, which has high utility value for design and maintenance of track structure.

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This paper explains the relation between road traffic conditions and acceleration noise, and makes the predictor model of acceleration which is explained from road traffic conditions and driver's performance. Then this paper proves the possibilities to predict the sections where traffic accidents happen frequently from the correlation of traffic accidents with the acceleration noise which in given by predictor model applied to other road. We show that this model contributes to the improvement of road traffic conditions for reducing traffic accidents.

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Different macroscopic approaches of estimating Passenger Car Equivalents (PCE) are evaluated first. Another approach is then introduced in which PCE is estimated by comparing flow rates at same percentage of capacity. Data from Tomei expressway (two lanes in each direction) are divided into various percentage of heavy vehicle class and PCE is estimated for each lane first. Unified PCE for both lanes is then calculated from distributions of total volume and heavy vehicle volume by lane. Results for different geometric conditions and direction of flow are also compared. PCE increases with increase in percentage of heavy vehicle to some maximum and decreases or remains almost constant afterwards.

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