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.
Files
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} }