skip to main content
10.1145/3316615.3316711acmotherconferencesArticle/Chapter ViewAbstractPublication PagesicscaConference Proceedingsconference-collections
research-article

An Automated Software-Agents System for Detecting Road Speed Limit Offences

Published: 19 February 2019 Publication History

Abstract

According to the statistical report of the Association of Safe International Road Travel (ASIRT), fatal road accidents are increasing because of fast driving. Many types of speed traps and cameras were installed by the road police departments at some parts of the roads trying to reduce the problem. Many drivers know where those cameras and speed traps are, so they reduce their speed when they are within the coverage of those cameras then, go back up to their previous speed again. This research proposes a system for smart cities or highways to control the problem via the placement of a set of Vehicular Ad-Hoc Network (VANET) devices on the roadside and within the vehicles to achieve side to side communication. The provided communication would be responsible for delivering real time information about the car, including its speed, which would help to detect the speeding offenders. By conducting this research, it is expected to identify the factors causing the accidents to happen, warn the speeding drivers at any time about their offence and to ensure a fine will be issued for every offender. In addition, the proposed system is expected to help traffic policemen in doing their job of identifying and proving that a driver has broken the road driving rules.

References

[1]
World Health Organization (WHO), "10 facts on global road safety", 2015. Online: http://www.who.int/features/factfiles/roadsafety/facts/en/index.html
[2]
"Transport, Local Government and the Regions - Ninth Report", House of Commons, United Kingdom, parliament Session 2001-02, Enforcement section. Online: https://publications.parliament.uk/pa/cm200102/cmselect/cmtlgr/557/ 55708.htm
[3]
Association of Safe International Road Travel (ASIRT), "Annual Global Road Crash Statistics", January 2016. Online: http://asirt.org/initiatives/informing-road-users/road-safety-facts/road-crash-statistics
[4]
Insurance Institute for Highway Safety, Highway Loss Data Institute, "General Statistics from the U.S. Department of Transportation's Fatality Analysis Reporting System (FARS): Status Report", February 2016. Online: http://www.iihs.org/iihs/topics/t/general-statistics/fatalityfacts/state-by-state-overview
[5]
Global Health Observatory (GHO), "Number of Road Traffic Deaths", 2010, Online: http://www.who.int/gho/road_safety/mortality/traffic_deaths_number/en/
[6]
World Health Organization (WHO), "Global status report on road safety 2013", 2013. Online: http://www.who.int/violence_injury_prevention/road_safety_status/2013/en/
[7]
International Traffic Safety Data and Analysis Group (IRTAD), "Road Safety Annual Report 2015", OECD Publishing, Paris. Online:
[8]
Rohayu Sarani, Sharifah Allyana Syed Mohamed Rahim, Jamilah Mohd Marjan, and Wong Shaw Voon. Research Report "Predicting Malaysian Road Fatalities for Year 2020", Malaysian Institution of Road Safety Research, 2012.
[9]
Harry Lum & Jerry A. Reagan (Winter 1995). "Interactive Highway Safety Design Model: Accident Predictive Module". Public Roads Magazine.
[10]
Yee Mun Lee, Siang Yew Chong, Karen Goonting, Elizabeth Sheppard, The effect of speed limit credibility on drivers' speed choice, Transportation Research Part F: Traffic Psychology and Behaviour, Volume 45, February 2017, Pages 43--53, ISSN 1369-8478.
[11]
C. Farkas, Y. Kopylova, "Application Level Protocol for Accident Reconstruction in VANETs", Master's Thesis, University of South Carolina, September 2007.
[12]
Bouziane Brik, Nasreddine Lagraa, Abderrahmane Lakas, Abbas Cheddad, DDGP: Distributed Data Gathering Protocol for vehicular networks, Vehicular Communications, Available online 4 February 2016, ISSN 2214-2096.
[13]
Renata Torquato Steinbakk, Pål Ulleberg, Fridulv Sagberg, Knut Inge Fostervold, Analysing the influence of visible roadwork activity on drivers' speed choice at work zones using a video-based experiment, Transportation Research Part F: Traffic Psychology and Behaviour, Volume 44, January 2017, Pages 53--62, ISSN 1369-8478.
[14]
C. Wietfeld and C. Ide, 1 - Vehicle-to-infrastructure communications, In Woodhead Publishing Series in Electronic and Optical Materials, edited by Wai Chen, Woodhead Publishing, 2015, Pages 3--28, Vehicular Communications and Networks, ISBN 9781782422112.
[15]
Sunilkumar S. Manvi, Shrikant Tangade, A survey on authentication schemes in VANETs for secured communication, Vehicular Communications, Volume 9, 2017, Pages 19--30, ISSN 2214-2096.
[16]
Satya S. Karanki, Mohammad S. Khan, SMMV: Secure multimedia delivery in vehicles using roadside infrastructure, Vehicular Communications, Volume 7, 2017, Pages 40--50, ISSN 2214-2096.
[17]
Maythem K. Abbas, Formal Specification Language for Vehicular Ad Hoc Network, Master's thesis, Universiti Teknologi PETRONAS, Department of Computer and Information Sciences, 2009.

Cited By

View all
  • (2023)Development and Testing Intelligent Video Surveillance Systems Based on the CNN AlgorithmProceedings of the Seventh International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’23)10.1007/978-3-031-43789-2_12(136-146)Online publication date: 21-Sep-2023

Index Terms

  1. An Automated Software-Agents System for Detecting Road Speed Limit Offences

    Recommendations

    Comments

    Information & Contributors

    Information

    Published In

    cover image ACM Other conferences
    ICSCA '19: Proceedings of the 2019 8th International Conference on Software and Computer Applications
    February 2019
    611 pages
    ISBN:9781450365734
    DOI:10.1145/3316615
    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]

    In-Cooperation

    • University of New Brunswick: University of New Brunswick

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 19 February 2019

    Permissions

    Request permissions for this article.

    Check for updates

    Author Tags

    1. Intelligent Transportation System (ITS)
    2. Vehicle-to-Road Side Communication (V2R)
    3. Vehicular Ad-hoc Network (VANET)
    4. road traffic control
    5. smart cities technologies

    Qualifiers

    • Research-article
    • Research
    • Refereed limited

    Conference

    ICSCA '19

    Contributors

    Other Metrics

    Bibliometrics & Citations

    Bibliometrics

    Article Metrics

    • Downloads (Last 12 months)10
    • Downloads (Last 6 weeks)0
    Reflects downloads up to 05 Mar 2025

    Other Metrics

    Citations

    Cited By

    View all
    • (2023)Development and Testing Intelligent Video Surveillance Systems Based on the CNN AlgorithmProceedings of the Seventh International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’23)10.1007/978-3-031-43789-2_12(136-146)Online publication date: 21-Sep-2023

    View Options

    Login options

    View options

    PDF

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader

    Figures

    Tables

    Media

    Share

    Share

    Share this Publication link

    Share on social media