• DocumentCode
    3605768
  • Title

    Trajectory Estimations Using Smartphones

  • Author

    Barrios, Cesar ; Motai, Yuichi ; Huston, Dryver

  • Author_Institution
    Dept. of Electr. Eng., Univ. of Vermont, Burlington, VT, USA
  • Volume
    62
  • Issue
    12
  • fYear
    2015
  • Firstpage
    7901
  • Lastpage
    7910
  • Abstract
    This paper investigates whether the smartphones´ built-in sensors can accurately predict future trajectories for a possible implementation in a vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) system. If smartphones could be used, vehicles without the V2V/V2I technology could use them to tap into the V2V/V2I infrastructure and help to populate the gap of vehicles off the V2V/V2I grid. To evaluate this, we set up a dead-reckoning system that uses Kalman filters to predict the future trajectory of a vehicle, information that could be used in a V2V/V2I system to warn drivers if the trajectories of vehicles will intersect at the same time. Then, we use a vehicle with accelerometer, GPS, and speedometer sensors mounted on it and evaluate its accuracy in predicting the future trajectory. Afterward, we place a smartphone securely on the vehicle´s dashboard, and we use its internal accelerometer and GPS to feed the same dead reckoning and Kalman filter setup to predict the future trajectory of the vehicle. We end by comparing both results and evaluating if a smartphone can achieve similar accuracy in predicting the future trajectory of a vehicle. Our results show that some smartphones could be used to predict a future position, but the use of their accelerometer sensors introduces some measurements that can be incorrectly interpreted as spatial changes.
  • Keywords
    Global Positioning System; Kalman filters; smart phones; traffic engineering computing; Kalman filters; accelerometer sensors; dead-reckoning system; smartphones; trajectory estimations; vehicle-to-infrastructure system; vehicle-to-vehicle system; Estimation; Global Positioning System; Sensor systems; Smart phones; Trajectory; Vehicles; Dead Reckoning; Dead reckoning; Kalman Filter; Kalman filter; Trajectory paths; position estimation; smartphones; trajectory paths; vehicle to infrastructure; vehicle to vehicle; vehicle-to-infrastructure (V2I); vehicle-to-vehicle (V2V);
  • fLanguage
    English
  • Journal_Title
    Industrial Electronics, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0278-0046
  • Type

    jour

  • DOI
    10.1109/TIE.2015.2478415
  • Filename
    7265042