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Yasuo Asakura

Other affiliations: Ehime University, Kobe University
Bio: Yasuo Asakura is an academic researcher from Tokyo Institute of Technology. The author has contributed to research in topics: Traffic flow & Traffic congestion. The author has an hindex of 22, co-authored 174 publications receiving 2745 citations. Previous affiliations of Yasuo Asakura include Ehime University & Kobe University.


Papers
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Journal ArticleDOI
TL;DR: This paper shows how existing methods such as the generalized least squares technique can be integrated with an equilibrium traffic assignment in the form of a convex bilevel optimization problem.
Abstract: Conventional methods for estimating origin-destination (O-D) trip matrices from link traffic counts assume that route choice proportions are given constants. In a network with realistic congestion levels, this assumption does not hold. This paper shows how existing methods such as the generalized least squares technique can be integrated with an equilibrium traffic assignment in the form of a convex bilevel optimization problem. The presence of measurement errors and time variations in the observed link flows are explicitly considered. The feasibility of the model is always guaranteed without a requirement for estimating consistent link flows from counts. A solution algorithm is provided and numerical simulation experiments are implemented in investigating the model's properties. Some related problems concerning O-D matrix estimation are also discussed.

356 citations

Journal ArticleDOI
TL;DR: A survey of highway TSE methods is conducted, and the recent usage of detailed disaggregated mobile data for the purpose of TSE is summarized, showing two possibilities in order to solve this problem: improvement of theoretical models and the use of data-driven or streaming-data-driven approaches, which recent studies have begun to consider.

304 citations

Journal ArticleDOI
TL;DR: The empirical data mining analysis showed that the proposed methodology can be applied to find and interpret the behavioural features observed in the smart card data which had been difficult to obtain from each independent dataset.
Abstract: The aim of this study is to develop a data fusion methodology for estimating behavioural attributes of trips using smart card data to observe continuous long-term changes in the attributes of trips. The method is intended to enhance understanding of travellers’ behaviour during monitoring the smart card data. In order to supplement absent behavioural attributes in the smart card data, this study developed a data fusion methodology of smart card data with the person trip survey data with the naive Bayes probabilistic model. A model for estimating the trip purpose is derived from the person trip survey data. By using the model, trip purposes are estimated as supplementary behavioural attributes of the trips observed in the smart card data. The validation analysis showed that the proposed method successfully estimated the trip purposes in 86.2% of the validation data. The empirical data mining analysis showed that the proposed methodology can be applied to find and interpret the behavioural features observed in the smart card data which had been difficult to obtain from each independent dataset.

227 citations

Journal ArticleDOI
TL;DR: The accuracy of the location positioning is found satisfactory for describing metropolitan scale travel behaviour and the proposed methodologies could be added in the toolbox of travel measurement.
Abstract: This paper shows the fundamental concepts and methodologies of using mobile communication instruments for tracking survey for individual travel behaviour in urban space. In particular, the characteristics of the tracking method using cellular phone are discussed. In addition to tracking type data collection procedure, the data transfer and labelling algorithms are proposed for providing various trip attributes to each point included in the location positioning data. The accuracy of the location positioning is found satisfactory for describing metropolitan scale travel behaviour. Tracking a hundred of event spectators has proved that the survey system would be available for on-line monitoring of a number of travellers in urban area. It is concluded that the proposed methodologies could be added in the toolbox of travel measurement.

207 citations


Cited by
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Christopher M. Bishop1
01 Jan 2006
TL;DR: Probability distributions of linear models for regression and classification are given in this article, along with a discussion of combining models and combining models in the context of machine learning and classification.
Abstract: Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

10,141 citations

Book ChapterDOI
30 May 2018
TL;DR: Tata Africa Services (Nigeria) Limited as mentioned in this paper is a nodal point for Tata businesses in West Africa and operates as the hub of TATA operations in Nigeria and the rest of West Africa.
Abstract: Established in 2006, TATA Africa Services (Nigeria) Limited operates as the nodal point for Tata businesses in West Africa. TATA Africa Services (Nigeria) Limited has a strong presence in Nigeria with investments exceeding USD 10 million. The company was established in Lagos, Nigeria as a subsidiary of TATA Africa Holdings (SA) (Pty) Limited, South Africa and serves as the hub of Tata’s operations in Nigeria and the rest of West Africa.

3,658 citations

Book
02 Jan 1991

1,377 citations

Journal ArticleDOI
TL;DR: Conventional approaches to chemical sensors have traditionally made use of a “lock-and-key” design, wherein a specific receptor is synthesized in order to strongly and highly selectively bind the analyte of interest.
Abstract: Conventional approaches to chemical sensors have traditionally made use of a “lock-and-key” design, wherein a specific receptor is synthesized in order to strongly and highly selectively bind the analyte of interest.1-6 A related approach involves exploiting a general physicochemical effect selectively toward a single analyte, such as the use of the ionic effect in the construction of a pH electrode. In the first approach, selectivity is achieved through recognition of the analyte at the receptor site, and in the second, selectivity is achieved through the transduction process in which the method of detection dictates which species are sensed. Such approaches are appropriate when a specific target compound is to be identified in the presence of controlled backgrounds and interferences. However, this type of approach requires the synthesis of a separate, highly selective sensor for each analyte to be detected. In addition, this type of approach is not particularly useful for analyzing, classifying, or assigning human value judgments to the composition of complex vapor mixtures such as perfumes, beers, foods, mixtures of solvents, etc.

1,192 citations

Journal ArticleDOI
TL;DR: The elasticity of travel demand is incorporated into the NDP and the economic‐based objective function for optimization is sought and the mixed network design problem involving simultaneous choice of link addition and capacity improvement is posed.

709 citations