Industrial Networks and Intelligent Systems. Second International Conference, INISCOM 2016, Leicester, UK, October 31 – November 1, 2016, Revised Selected Papers

Research Article

An Improved Robust Low Cost Approach for Real Time Vehicle Positioning in a Smart City

  • @INPROCEEDINGS{10.1007/978-3-319-52569-3_7,
        author={Ikram Belhajem and Yann Ben Maissa and Ahmed Tamtaoui},
        title={An Improved Robust Low Cost Approach for Real Time Vehicle Positioning in a Smart City},
        proceedings={Industrial Networks and Intelligent Systems. Second International Conference, INISCOM 2016, Leicester, UK, October 31 -- November 1, 2016, Revised Selected Papers},
        proceedings_a={INISCOM},
        year={2017},
        month={6},
        keywords={Data fusion Extended kalman filter Global positioning system Intelligent transportation systems Smart cities Dead reckoning Low cost Neural networks Particle swarm optimization},
        doi={10.1007/978-3-319-52569-3_7}
    }
    
  • Ikram Belhajem
    Yann Ben Maissa
    Ahmed Tamtaoui
    Year: 2017
    An Improved Robust Low Cost Approach for Real Time Vehicle Positioning in a Smart City
    INISCOM
    Springer
    DOI: 10.1007/978-3-319-52569-3_7
Ikram Belhajem1,*, Yann Ben Maissa1,*, Ahmed Tamtaoui1,*
  • 1: National Institute of Posts and Telecommunications
*Contact email: belhajem@inpt.ac.ma, benmaissa@inpt.ac.ma, tamtaoui@inpt.ac.ma

Abstract

The Global Positioning System (GPS) aided low cost Dead Reckoning (DR) system can provide without interruption the vehicle position for efficient fleet management solutions in smart cities. The Extended Kalman Filter (EKF) is generally applied for data fusion using the sensor’s measures and the GPS position as a helper.