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Evidence-based automated traffic hazard zone mapping using wearable sensors

Published: 08 November 2010 Publication History

Abstract

Recently, underestimating traffic condition risk is considered one of the biggest reasons for traffic accidents. In this paper, we proposed evidence-based automatic hazard zone mapping method using wearable sensors. Here, we measure driver's behavior using three-axis gyro sensors. Analyzing the measured motion data, proposed method can label characteristic motion that is observed at hazard zone. We gathered motion data sets form two types of driver, i.e., an instructor of driving school and an ordinary driver, then, tried to generate traffic hazard zone map focused on difference of the motions. Through the experiment in public road, we confirmed our method allows to extract hazard zone.

References

[1]
Traffic bureau, National police agency, Report of traffic accident in 2010, Feb. 25, 2010.
[2]
Z. Sun, Z. Yang, "A GIS System for Managing and Analyzing Urban Road Traffic Accident", Proc. of the Eastern Asia Society for Transportation Studies, Vol. 4, pp. 1442--1449, 2003
[3]
L. Y. Liang, D. M. Masoem, L. T. Hua, "Traffic Accident Application Using Geographic Information System", Journal of the Eastern Asia Society for Transportation Studies, Vol. 6, pp. 3574--3589, 2005.
[4]
S. E. Gholston, M. D. Anderson, "A GIS accident system to accompany CARE", UTCA Report 03304, 2005.
[5]
F. Naya, R. Ohmura, H. Noma and K. Kogure, "Worker' s Routine Activity Recognition using Body Movements and Location Information", Proc. of IEEE International Symposium on Wearable Computer 2006, pp. 105--108.

Cited By

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  • (2021)Dependability and Safety: Two Clouds in the Blue Sky of Multimodal InteractionProceedings of the 2021 International Conference on Multimodal Interaction10.1145/3462244.3479881(781-787)Online publication date: 18-Oct-2021

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cover image ACM Conferences
ICMI-MLMI '10: International Conference on Multimodal Interfaces and the Workshop on Machine Learning for Multimodal Interaction
November 2010
311 pages
ISBN:9781450304146
DOI:10.1145/1891903
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 08 November 2010

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Author Tags

  1. driving behavior analysis
  2. gyro sensor
  3. traffic hazard map
  4. wearable sensor

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ICMI-MLMI '10 Paper Acceptance Rate 41 of 100 submissions, 41%;
Overall Acceptance Rate 453 of 1,080 submissions, 42%

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Cited By

View all
  • (2021)Dependability and Safety: Two Clouds in the Blue Sky of Multimodal InteractionProceedings of the 2021 International Conference on Multimodal Interaction10.1145/3462244.3479881(781-787)Online publication date: 18-Oct-2021

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