Interdisciplinary Information Sciences
Online ISSN : 1347-6157
Print ISSN : 1340-9050
ISSN-L : 1340-9050
Volume 21, Issue 1
Displaying 1-7 of 7 articles from this issue
Regular Paper
  • Miyuki SAKURAI, Syoichi IWASAKI
    2015 Volume 21 Issue 1 Pages 1-10
    Published: 2015
    Released on J-STAGE: December 13, 2014
    JOURNAL FREE ACCESS
    This study investigated the effect of aging on the dual task interference when an auditory task of answering to questions was combined with a visual search task. The study focused on the effect of unilateral auditory input, which is usually the case when we use cellular phone by applying it to one ear while driving. Participant's task was to detect a probe from among distracters. In the dual task condition, participant detected the probe, while listening to a simple open-ended question. Both younger and older participants showed comparable dual task interference in detection RT. In the older participants, however, the auditory task interfered with the probe detection more when they heard the questions with their left ear than when they did so with their right ear, suggesting that the dual task cost was especially large when they answered to question heard from their left ear.
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Special Section: Nowcast and Forecast of Road Traffic by Data Fusion of Various Sensing Data
  • Shun KATAOKA, Muneki YASUDA, Kazuyuki TANAKA
    2015 Volume 21 Issue 1 Pages 11-23
    Published: 2015
    Released on J-STAGE: March 20, 2015
    JOURNAL FREE ACCESS
    We focus on an interpolation method referred to Bayesian reconstruction in this paper. Whereas in standard interpolation methods missing data are interpolated deterministically, in Bayesian reconstruction, missing data are interpolated probabilistically using a Bayesian treatment. In this paper, we address the framework of Bayesian reconstruction and its application to the traffic data reconstruction problem in the field of traffic engineering. In the latter part of this paper, we describe the evaluation of the statistical performance of our Bayesian traffic reconstruction model using a statistical mechanical approach and clarify its statistical behavior.
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  • Takashi HASEGAWA, Takehiro ITO, Akira SUZUKI, Xiao ZHOU
    2015 Volume 21 Issue 1 Pages 25-35
    Published: 2015
    Released on J-STAGE: March 20, 2015
    JOURNAL FREE ACCESS
    For a digraph G = (V,A) and a source vertex sV, suppose that we wish to compute a shortest directed path from s to every vertex vV \ {s} (if exists) under several arc costs. Frigioni et al. (2000) proposed a dynamic algorithm which efficiently reuses the shortest-paths information computed for the previous arc costs. In this paper, we experimentally evaluate how such a dynamic algorithm works efficiently for real-world networks.
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  • Kazuyuki NARISAWA, Takashi KATSURA, Hiroyuki OTA, Ayumi SHINOHARA
    2015 Volume 21 Issue 1 Pages 37-47
    Published: 2015
    Released on J-STAGE: March 20, 2015
    JOURNAL FREE ACCESS
    Multi-track data are multi-set sequences that are suitable for representing time series data, such as multi-sensor data, polyphonic music data and traffic data. The permuted pattern matching problem aims to determine the occurrences of multi-track patterns in multi-track text by allowing the order of the pattern tracks to be permuted. In this study, we address permuted pattern matching by proposing a new data structure called a filtering multi-set tree (FILM tree). The FILM tree is a complete binary tree based on a spectral Bloom filter (SBF) with hash functions. This data structure is very simple but powerful, and it can be applied to both exact and approximate matching problems. We present experimental results that demonstrate the efficiency of our FILM tree-based approach.
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  • Peng fei WANG, Kentaro WADA, Takashi AKAMATSU, Yusuke HARA
    2015 Volume 21 Issue 1 Pages 49-61
    Published: 2015
    Released on J-STAGE: March 20, 2015
    JOURNAL FREE ACCESS
    The purpose of this paper is to explore the features of the Macroscopic Fundamental Diagram (MFD) for Sendai road networks. In order to achieve this, we used the observed data of 5-minute periods throughout one year (5/1/2012–4/30/2013) to draw the MFDs for Sendai road networks. The result of the empirical verification shows the following: (1) the hysteresis loops always form in an MFD on weekdays with good weather, and their formation times correspond to the peak hours of the morning and evening; (2) the shape of the MFD is invariant throughout the year; (3) loops do not form on Sundays (or holidays) when the peak of traffic demand is lower than on weekdays; (4) loops that are larger than those in a typical MFD form when the driving environment is poor; and (5) if the analysis area for drawing the MFD shrinks, then the variation of the MFD expands.
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  • Masao KUWAHARA
    2015 Volume 21 Issue 1 Pages 63-75
    Published: 2015
    Released on J-STAGE: March 20, 2015
    JOURNAL FREE ACCESS
    This study first summarizes the Kinematic Wave Theory which has been used to describe vehicle motions and the Variational Theory which is an efficient solution method to estimate vehicle trajectories based on the Kinematic Wave Theory. Then, several demonstrative applications on a signalized arterial and on an intercity motorway are presented by a data fusion technique using probe vehicle data and conventional traffic detector data.
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  • Kentaro WADA, Takeshi OHATA, Keiko KOBAYASHI, Masao KUWAHARA
    2015 Volume 21 Issue 1 Pages 77-85
    Published: 2015
    Released on J-STAGE: March 20, 2015
    JOURNAL FREE ACCESS
    Probe data provide rich information of vehicle trajectories which include driving modes (e.g., acceleration/deceleration) and reflect traffic conditions. However, most of the applications only use probe data to measure travel times. This paper presents two alternative applications of vehicle trajectories on signalized arterials: one is a traffic signal timing estimation and the other is a traffic volume estimation. Both applications are based on a simple methodology that combines vehicle trajectories and traffic engineering concept shock wave. By testing the methodology using real world data, we demonstrate that probe data have more potential for traffic measurements.
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