Real Time Vehicle Trajectory Estimation on Multiple Lanes

Abstract

Today’s road traffic management systems using intelligent transportation systems solutions need real time measurements of various traffic parameters like flow, origin-destination matrices, vehicle type, etc. Cameras combined with image processing algorithms are being more and more used as the sensor capable to measure several traffic parameters. One such parameter, also important for accurate simulation of road traffic flow and evaluation of traffic safety, is the driving aggressiveness factor which can be estimated from the vehicles trajectory. In this paper an Extended Kalman Filter based approach to estimate vehicle trajectories on multiple lanes using only one static camera is described. To test the accuracy of the implemented approach a synthetic road traffic environment is developed. Real time capabilities of the approach are tested using real traffic video footage obtained from Croatian highways.

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BibTeX Citation

DOI

10.20532/ccvw.2014.0008

https://doi.org/10.20532/ccvw.2014.0008

BibTeX

@InProceedings{10.20532/ccvw.2014.0008,
  author =       {Kristian Kova{\v c}i{\' c} and Edouard Ivanjko and
                  Hrvoje Gold},
  title =        {Real Time Vehicle Trajectory Estimation on Multiple
                  Lanes},
  booktitle =    {Proceedings of the Croatian Compter Vision Workshop,
                  Year 2},
  pages =        {21-26},
  year =         2014,
  editor =       {Lon{\v c}ari{\' c}, Sven and Suba{\v s}i{\' c},
                  Marko},
  address =      {Zagreb},
  month =        {September},
  organization = {Center of Excellence for Computer Vision},
  publisher =    {University of Zagreb},
  abstract =     {Today’s road traffic management systems using
                  intelligent transportation systems solutions need
                  real time measurements of various traffic parameters
                  like flow, origin-destination matrices, vehicle
                  type, etc. Cameras combined with image processing
                  algorithms are being more and more used as the
                  sensor capable to measure several traffic
                  parameters. One such parameter, also important for
                  accurate simulation of road traffic flow and
                  evaluation of traffic safety, is the driving
                  aggressiveness factor which can be estimated from
                  the vehicle’s trajectory. In this paper an Extended
                  Kalman Filter based approach to estimate vehicle
                  trajectories on multiple lanes using only one static
                  camera is described. To test the accuracy of the
                  implemented approach a synthetic road traffic
                  environment is developed. Real time capabilities of
                  the approach are tested using real traffic video
                  footage obtained from Croatian highways.},
  doi =          {10.20532/ccvw.2014.0008},
  url =          {https://doi.org/10.20532/ccvw.2014.0008}
}