On Request Autonomous Vehicle Application
J.M Armingol, J. E. Naranjo, F. Jimenes, A. de la Escalera, F. Garcia, D. Gomez, A. Al Kaff, A. Hussein, P. Marin, F. M. Moreno , J. Beltran, C. Guindel and M. A. de Miguel.

Perception framework

 The vehicles of the intelligent system lab will show their advances in data fusion and enhanced perception, based on Lidar and computer vision for environment understanding, mapping and localization.

 Experimental set up & Demonstration

  • The  autonomous vehicle receives a communication from the pedestrian, performing a vehicle request.
  • The car, driven by itself moves to the location of the passenger.
  • Passenger get in and confirms the pick up in the vehicle.
  • Vehicle moves to the desired location
  • Passenger gets off and the vehicle is ready to repeat this process again.

During the path, and in the demonstration site, the vehicles will display the obstacle detection and classification, as well as the environment reconstruction.

[1] Automatic Extrinsic Calibration for Lidar-Stereo Vehicle Sensor Setups. Guindel, C., Beltran J., Martin Gomez, D., Garcia F., 2017 IEEE International Conference on Intelligent Transportation Systems, Yokohama, japan, 16-19 October, 2017. [PDF]
[2] Market-based Approach for Cooperation and Coordination Among Multiple Autonomous Vehicles, Kőkuti, A., Hussein, A., de la Escalera, A., Garcia, F. 2017 IEEE International Conference on Intelligent Transportation Systems. Workshop Artificial Transportation Systems and Simulation, Yokohama, Japan, 16-19 October, 2017.
[3] Hybrid Optimization-Based Approach for Multiple Intelligent Vehicles Requests Allocation, Journal of Advanced Transportation, vol. 2018, Article ID 2493401, 11 pages, 2018. doi:10.1155/2018/2493401. [PDF]
[4] Al-Kaff, A., Martín, A., García, F., de la Escalera, A., Armingol, J. M., Survey of Computer Vision Algorithms and Applications for Unmanned Aerial Vehicles, In Expert Systems with Applications, 2017, ISSN 0957-4174, pp 447-463 https://doi.org/10.1016/j.eswa.2017.09.033. Q1(2016).
[5] García, F,, Prioletti, A., Cerri, P., Broggi, A., PHD filter for vehicle tracking based on a monocular camera, In Expert Systems with Applications, Volume 91, 2018, Pages 472-479, ISSN 0957-4174, https://doi.org/10.1016/j.eswa.2017.09.018. Q1(2016).
[6] Garcia, F., Martin, D., de la Escalera, A., & Armingol, J. M. (2017). Sensor fusion methodology for vehicle detection. IEEE Intelligent Transportation Systems Magazine, 9(1), 123-133. Q1 (2016).