A Civil infrastructure is built through the prolonged process of plan, investigation, design, construction, and operation and maintenance, and drawings are taken over in each process. Drawing data of structures are generated in a design phase using CAD (Computer Aided Design) software. The design intention of a structure like the use function of CAD software, and a model generation procedure is expressed in CAD data. Therefore, it can be necessary to use it in construction or operation and maintenance phase. Moreover, in a construction project, although building the environment where three-dimensional data is used for CIM (Construction Information Modeling), information integrated construction, and an improvement in productivity is requested, the three-dimensional CAD which fills these requests does not exist.
In this paper, the three-dimensional CAD engine for creating the three-dimensional CAD data holding the design intention of an infrastructure was developed. The three-dimensional CAD engine developed fulfills the needs concerning infrastructure, such as adoption of parametric modeling, consideration of a time, and conformity of the International Standard. Moreover, the three-dimensional CAD system for verifying to construct three-dimensional CAD data of civil infrastructure was developed. The experiments using three-dimensional CAD engine and system showed that they are adapted to generate three-dimensional CAD data in civil infrastructure construction projects.

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For analysis of influence on traffic environment change, a traffic simulation model is used. In the study, the carfollowing model that is the important component of the traffic simulation is examined. In the ordinary traffic simulation model, a numerical formula model is used as a car-following model. In the study, the applicability of the fuzzy neural network model is examined. In the existing study, the fuzzy neural network model is developed using the running survey data. In the study, the applicability of the car-following model is examined. As a result, the model using the fuzzy neural network can be estimated in a small error then a conventional non-linear car-following model. As s result of examination using the traffic simulation model, the difference of the result by the model is observed.

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In the infrastructure planning, the research field is extended to the mental health additionally to the economic oriented social system planning. The mental analysis gives the impact to creation of identity of civil engineers as well as self-organized mentality of citizens expected in urban planning and transport planning. In the study, the analysis of depth psychology is introduced to develop the mental planning in infrastructure planning. Actually, the knowledge base system for diagnosis system of "Baum test" (tree test) to recognize the personality of younger generation. In particular, the production system is developed with inference engine based on the knowledge of experience to describe the process of interpret the mentality in depth reflecting the projection of tree. Furthermore, the neural network is applied to develop the estimation model to indicate the relation between actual psychoactive and inner mentality. The application of intelligent information processing to clinical psychology provides the direction to solve the problem of mentalities in the social system.

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Rivers are managed by preparing materials including various drawings and registers. In particular, cross sections are very important materials because they are used for not only grasping the current conditions of levees but also river improvement plans and so on. However, since cross sections are surveyed and made into drawings by human operation, they are created only on the distant posts at 200m intervals due to limitations of survey costs. Currently, therefore, a technology for generating cross sections from LP data acquired by airborne laser surveying is needed. However, there are some problems for LP data ; that they contain noises of vegetation and so on which disturb ground surface survey, and that it is impossible to measure changing points of cross sections due to the problem of point cloud density. Existing researches on dealing with the problems for LP data include a method of extracting point cloud data of the ground surface by obtaining the lowest point at every specific range from LP data, and a method of estimating break lines from LP data. However, the former has "a problem that the accuracy of point cloud data is dependent on the grid width" and the latter "a problem that it makes an error in extraction of a break line at bends". To solve these two problems, this research proposes a method for noise reduction which is independent of grid width, and a method for estimating break lines properly at bends as well. In order to prove usefulness of the proposed methods, evaluation experiments were conducted to compare the cross sections of proposed methods with those of existing methods, and evaluated them.

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Many highway bridges constructed during the high economic growth period have become deteriorated. So their maintenance is required. However, they are facing difficulties in maintenance because their drawings prepared at the time of design or completion were made in paper media, many of which have already been disposed. There is a research that attempts to automatically generate SXF (Scadec data eXchange Format) drawings of a highway bridge to use for its maintenance, using point cloud data obtained by MMS (Mobile Mapping System). In the previous research, the authors use positions of joints on a bridge to divide a point sequence into each span and generate their alignments of the highway bridge. However, when it is unable to extract a joint, or when the start and end points of the alignment are placed at a short distance from the positions of joints on a design drawing, the generated clothoid curve will lose continuity with straight line and circular arc. Thus, this research proposes an analysis method for calculating the start and end points of straight lines, clothoid curves, and circular arcs in a plane and straight lines and quadratic curves in a longitudinal section to allow each alignment to connect with each other naturally. This allows generating the SXF drawings of the superstructure on a highway bridge with high precision without considering the positions of joints.

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Multi-agent simulation approach is suitable to describe the heterogeneity on social interaction. The choice of clean energy vehicle corresponding to the promoting policy related to economic incentive or innovation of vehicle is estimated with the multi-agent simulation. The proposed multi-agent simulation system consists of the vehicle choice model and the social interaction model. The vehicle choice is affected by social conformity effect in the model. The relation between agents like a social network of the real world is generated with a simple algorithm by small world network model. The time series changes of the number of the clean energy vehicle and the volume of greenhouse gas emission are estimated by proposed multi-agent simulation.

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Smart phone allows easy acquisition of pedestrian trip data. Consequently, it is expected that pedestrian trip data will be utilized in some fields such as disaster response and transportation. Depending on the uses such as disaster situations, accurate pedestrian trip data on the real-time basis is required. However, the location information acquired from GPS sensor of respective smart phone exhibit unevenness in the accuracy and contain plenty of noises since they differ from each other depending on the surrounding environments or models. There is a possibility that analysis of enormous amounts of pedestrian trip data can handle the problem mentioned above. However, this is not satisfactory for the uses in emergency as it lacks real-time performance. In this research, we devised a method of noise reduction by using PDOP, circular error probability, and pedestrian trip data in order to acquire three-dimensional location information with high certainty in real time from pedestrian trip data acquired by smart phone. Then this method was applied to the probe-person research data to verify its usefulness.

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In recent years, there have been growing needs for computers which comprehend what is meant in humorous texts. However, we have few examples of research that have tried to detect puns from a large corpora of spoken language. A sampling survey of typology and component ratio analysis in Japanese puns revealed that the type of Japanese pun that had the largest proportion was a pun type with two sound sequences, whose consonants are phonetically close to each other in the same sentence which includes the pun. Based on this finding, we constructed three rules to detect pairs of phonetically similar sequences, and used them as features for SVM. Using these features in addition to bag-of-words features, an evaluation experiment confirmed the effectiveness of adding the three phonetic similarity features to the baseline classifier.

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