• DocumentCode
    186180
  • Title

    Detection of Vulnerable Road Users in Smart Cities

  • Author

    Guayante, Francisco ; Diaz-Ramirez, Arnoldo ; Mejia-Alvarez, Pedro

  • Author_Institution
    Dept. of Comput. Syst., Inst. Tecnol. de Mexicali, Mexicali, Mexico
  • fYear
    2014
  • fDate
    10-12 Sept. 2014
  • Firstpage
    307
  • Lastpage
    312
  • Abstract
    Starting from 2008, more than half of the world´s population now lives in urban areas, and this number is expected to grow for the next decades. To the extent that the population of a city grows, new problems arise, which include scarcity of resources, pollution, and traffic congestion. One of the most important problems of big cities are road traffic injuries, which is the eighth leading cause of death globally, and the main cause of death for young people, mainly in middle and low income countries. Vulnerable road users (VRUs) are among the users at higher risks of traffic accidents. In order to cope with the problems of the growing urban communities, the concept of smart cities has emerged. A smart city is based on the use of smart computing technologies, such as Intelligent Transportation Systems and Vehicular Ad hoc Networks. In this paper, we propose a model to be used in smart cities, to detect if a VRU intends to cross a road in a risky zone, and to issue alerts to the vehicles nearby. The proposed model is cost effective, and is able to detect a VRU at risk in a short period of time. The evaluation of the proposed model shows that it performs correctly.
  • Keywords
    road accidents; road traffic; smart cities; traffic engineering computing; VRU; smart cities; smart computing; traffic accidents; vulnerable road user detection; Cities and towns; Roads; Temperature distribution; Temperature measurement; Temperature sensors; Vehicles; Smart Cities; VANETs; VRUs detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Next Generation Mobile Apps, Services and Technologies (NGMAST), 2014 Eighth International Conference on
  • Conference_Location
    Oxford
  • Print_ISBN
    978-1-4799-5072-0
  • Type

    conf

  • DOI
    10.1109/NGMAST.2014.60
  • Filename
    6982933