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  1. International Journal of Intelligent Transportation Systems Research
  2. International Journal of Intelligent Transportation Systems Research : Volume 15
  3. International Journal of Intelligent Transportation Systems Research : Volume 15, Issue 3, September 2017
  4. Analysis of Accident Risks from Driving Behaviors
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International Journal of Intelligent Transportation Systems Research : Volume 15
International Journal of Intelligent Transportation Systems Research : Volume 15, Issue 3, September 2017
Extension of Cellular Automata for Dynamic Vehicle Tracking
On Software-based Remote Vehicle Monitoring for Detection and Mapping of Slippery Road Sections
Estimation of Required EVs Battery Capacity for Leveling Demand Energy Considering Parking Durations
Safe and Environment-Friendly Forward Collision Warning Messages in the Advance Warning Area of a Construction Zone
Estimation of Scaling Factors for Traffic Counts Based on Stationary and Mobile Sources of Data
Analysis of Accident Risks from Driving Behaviors
International Journal of Intelligent Transportation Systems Research : Volume 15, Issue 2, May 2017
International Journal of Intelligent Transportation Systems Research : Volume 15, Issue 1, January 2017
International Journal of Intelligent Transportation Systems Research : Volume 14
International Journal of Intelligent Transportation Systems Research : Volume 13
International Journal of Intelligent Transportation Systems Research : Volume 12
International Journal of Intelligent Transportation Systems Research : Volume 11
International Journal of Intelligent Transportation Systems Research : Volume 10
International Journal of Intelligent Transportation Systems Research : Volume 9
International Journal of Intelligent Transportation Systems Research : Volume 8

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Analysis of Accident Risks from Driving Behaviors

Content Provider Springer Nature Link
Author Osafune, Tatsuaki Takahashi, Toshimitsu Kiyama, Noboru Sobue, Tsuneo Yamaguchi, Hirozumi Higashino, Teruo
Copyright Year 2016
Abstract Detecting aggressive driving behavior is essential for safe transport systems as it leads to the awareness of risks of accidents. Using smartphone-equipped sensors would be promising approach considering the penetration ratio to the consumers. In this paper, we have used a large dataset of accelerometer readings collected by smartphones of drivers. The experiment was performed to explore the accident risk indexes which statistically separate the safe drivers and risky drivers. By the statistical analysis, it is found that the frequency of acceleration exceeding 2.4 m/s$^{2}$, that of deceleration exceeding 1.4 m/s$^{2}$, and that of left acceleration exceeding 1.1 m/s$^{2}$ separate the safe drivers and risky drivers. The classifier using these three criteria achieves 70 % classification accuracy and 83 % detection accuracy of risky drivers.
Starting Page 192
Ending Page 202
Page Count 11
File Format PDF
ISSN 13488503
Journal International Journal of Intelligent Transportation Systems Research
Volume Number 15
Issue Number 3
e-ISSN 18688659
Language English
Publisher Springer US
Publisher Date 2016-09-01
Publisher Place New York
Access Restriction One Nation One Subscription (ONOS)
Subject Keyword Driver behavior Smartphone Insurance telematics Pay how you drive Usage-based insurance Electrical Engineering Automotive Engineering Robotics and Automation Computer Imaging, Vision, Pattern Recognition and Graphics Civil Engineering User Interfaces and Human Computer Interaction
Content Type Text
Resource Type Article
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