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On Software-based Remote Vehicle Monitoring for Detection and Mapping of Slippery Road Sections

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Abstract

The use of vehicular communications and networking technology has started to open up endless possibilities for applications development. These efforts include a wide rage of applications from road maintenance and traffic engineering at the transportation engineering level to applications designed for personal convenience and entertainment. In this paper, we describe our project on monitoring road conditions supported by the DOT-RITA program and the various agencies in Anchorage, Alaska. Our project first focuses on identifying dangerous road sections typically caused by, but not limited to, ice patches using vehicle slippage detection. The detection was done through probe vehicles equipped with our custom vehicular interface and networking device called CANOPNR (CAN-BUS OBD Programmable-expandable Network-enabled Reader). We describe the details of the CANOPNR architecture as well as our algorithm for slippage detection and present our test results. Along with the hardware configuration, our software has also been made openly available for the research community to use. Our test results showed that the system is able to effectively identify slippery road sections. We were also able to show the potential for prediction of some accident-prone areas. Individual cities may significantly benefit from utilizing such methodology with existing service vehicles as well as with the participation by the public. The end-users can benefit from safer-route computations enabled by the mappings.

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Notes

  1. As a side note, for any methodology to provide formal validation, a complete scan of all of city’s road sections (of interest) would be required, which, short of physical testing, in itself would raise questions about how that data was generated.

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Acknowledgments

This work was supported in part by USDOT-RITA Grant #00003238 (AUTC Project #510018 Miller, Kim, Ali), by General Communications Inc, and the University of Alabama in Huntsville NFR grant. We would also like to acknowledge support from the Municipality of Anchorage, and assistance provided by Mr. Kelly Smith and the staff of the University of Alaska Anchorage Automotive and Diesel Technology Department, and the Anchorage Police Department. The views presented in this paper are of the authors only and do not necessarily reflect that of the supporting organizations.

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Authors and Affiliations

  1. InfoSpace, 10900 NE 8th St #800, Bellevue, WA, 98004, USA

    Denrie Enriquez Jr.

  2. Department of Mechanical Engineering, Ohio University, Athens, OH, 45701, USA

    Sean Jenson & Muhammad Ali

  3. General Communications Incorporated, Anchorage, AK, USA

    Alex Bautista & Paloma Hawn

  4. Computer Science Department, North Central College, Naperville, IL, USA

    Sun-il Kim

  5. Department of Computer Science, University of Southern California, Los Angeles, CA, USA

    Jeffrey Miller

Authors
  1. Denrie Enriquez Jr.
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  2. Sean Jenson
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  3. Alex Bautista
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  4. Paloma Hawn
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  5. Sun-il Kim
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  6. Muhammad Ali
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  7. Jeffrey Miller
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Corresponding author

Correspondence to Sun-il Kim.

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Enriquez, D., Jenson, S., Bautista, A. et al. On Software-based Remote Vehicle Monitoring for Detection and Mapping of Slippery Road Sections. Int. J. ITS Res. 15, 141–154 (2017). https://doi.org/10.1007/s13177-016-0128-9

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  • DOI: https://doi.org/10.1007/s13177-016-0128-9

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