Takamasa Akiyama

Development of the Microscopic Traffic Simulation Model with the Fuzzy Logic technique

Microscopic traffic simulation (MTS) has attracted increasing attention in the last two decades as it analyzes individual vehicle/driver behavior more precisely and realistically than other methods. MTS is nothing but a series of human decisions under various traffic situations. Since human element is involved at many stages of simulation, the possibility of approximation/error in the decisions would be high. In this direction, the fuzzy logic technique appropriately takes such approximations into account while modeling drivers’ decisions. Some of the MTS models have considered fuzzy logic in at most one or two models, such as car following, lane change behavior, etc., with limited urban congested conditions. However, human involvement exists beyond these and realistic output from the simulation would not be possible unless the approximations involved at different stages are appropriately and simultaneously considered. In the present study, a Fuzzy Logic based Microscopic Traffic Simulation Model (FLoMiTSiM) to describe human behavior on the urban road network in many possible situations is proposed and appropriately validated using the observed data from the city of Gifu, Japan. To demonstrate the applicability and suitability of the proposed FLoMiTSiM, bus priority policies, namely bus lanes, are evaluated.

Estimation of time-varying origin-destination flows from traffic counts: A neural network approach

A dynamic model based on the error back-propagation learning principle in neural network theory is proposed for estimating origin-destination flows from the road entering and exiting counts in a transportation network. The origin-destination flows in each short time interval are estimated through minimization of the squared errors between the predicted and observed exiting counts which are normalized using a logistic function. Two numerical experiments are conducted to evaluate the performance of the proposed model; one uses a typical four-way intersection, and the other one uses a real freeway section. Numerical results show that the back-propagation based model is capable of tracking the time variations of the origin-destination flows with a high stability.

FUZZY MATHEMATICAL PROGRAMMING FOR TRAFFIC SAFETY PLANNING ON AN URBAN EXPRESSWAY

Traffic safety planning has received increased attention because a number of accidents still occur on urban area transportation networks. The optimization approach, using budget constraints, is applicable to many problems of infrastructure planning that must be carried out under these circumstances. The problems of choosing which traffic safety facilities to construct on urban expressways are investigated in this study. This type of economic problem is formulated as an optimization of combinations problem. Incremental benefit‐cost analysis and Dynamic Programming using fuzzy budget constraints are introduced. Particularly, the standard algorithm normally used to solve this problem is modified, because the fuzzy goal is defined as a step function in this type of problem. In addition, the shapes of the membership functions of fuzzy constraints are also discussed. The facts from a case study of the Hanshin Expressway (in the Kansai area of Japan) will be presented to illustrate how fuzzy theory improves the ...

Travel time information service device based on fuzzy sets theory

Drivers on highways usually can obtain predicted travel time information through a traffic control system in Japan. Information processing for the proper description of the travel time is discussed. A device based on fuzzy set theory is considered to transform forecasted values into practical traffic information. Drivers perception concerned with an allowable gap between a real travel time and an informed travel time was observed in a survey. The type of fuzzy number is defined according to the traffic condition. Three methods are introduced to choose the proper description of the travel time from the database of acquired knowledge of drivers. The performance of the proposed device is evaluated to improve the data processing technique. Real data is used to find a satisfactory method to modify the device.<<ETX>>

A Logit Model for Modal Choice with a Fuzzy Logic Utility Function

It is important in travel behaviour analysis to construct precise activity based models. A knowledge based-approach using fuzzy logic has been applied to create an advanced model combined with a stochastic approach. The advantage of the hybrid model will be discussed. The application of the model to modal choice problems is described in this paper.

Construction of modal choice model with a descriptive utility function using fuzzy reasoning

It is important in travel behaviour analysis to construct precise discrete choice models. Stochastic models based on the random utility theory such as logit models and fuzzy reasoning models can be combined in order to create advanced models for the estimation of travel behaviour as hybrid models. Particularly, logit models with fuzzy logic utility functions have been proposed. It is known that the utility function described with fuzzy inference rules can reflect human decisions with vagueness on the logit models. Multinominal fuzzy logit models are applied to a modal choice problem in this study. In particular, the fuzzy inference rules and parameters of membership functions are determined using GA.

Application of Fuzzy Decision Tree to Analyze the Attitude of Citizens for Wellness City Development

The attitudes of citizens would be analyzed to design the future wellness city. The fuzzy decision tree is applied to describe the decision structure concerning with individual health as well as participation in the project. The questionnaire survey is taken to the citizens relating with the real wellness city project. The decision tree analysis such as ID3, fuzzy ID3 are introduced to describe the structure of decision of citizens. According to the results of fuzzy ID3 analysis, the difference between the attitudes of individual health and that of community health. Furthermore, linguistic decision rules are summarized to realize the future design of the wellness city.

Multi-agent simulator in transport sector for low carbon society

The carbon dioxide emission of transport section is an important issue to realize the low carbon society. In the study, the multi-agent simulation model is developed to evaluate the transport policy. The decision models of trip makers for modal choice and car ownership are formulated to estimate the impact of transport policy in the artificial society. In particular, the agent decision of electric vehicles (EV) ownership is assumed to be influenced by the surrounding ecological environment. These decision models are described by fuzzy logic. The reduction process of carbon dioxide (CO2) emission can be observed in time series diagrams as well as the distribution on individual wards. Finally, it is concluded that the low carbon society is realized by introducing the electric vehicles with particular regulations.

Development and verification of estimation model of environmental impact of automobile

In this study, a carbon dioxide emission is estimated corresponding to the running condition of the vehicle in the real field. The volume of carbon dioxide emission is measured during driving vehicles. Furthermore, the method of estimating the carbon dioxide emissions is proposed. In particular, it is validated the reliability of existing methods for measurement the CO2 emissions using the data obtained from the engine controller and the amount of gasoline consumption. In addition, the relationship between the running pattern and the carbon dioxide emission is analyzed.

Analysis of Railway User Travel Behaviour Patterns of Different Age Groups

This study presents an analysis of travel behavior patterns of different age groups of urban railway users in the Keihanshin metropolitan area of Japan. The objective is to examine the relationship between urban public transportation use and urban activities. The study examines urban activities within aging societies, focusing on the differences in travel behavior of railway users by age groups.