Arquitectura dual-modular para desarrollos y validación de módulos de decisión y control en vehículos automatizados

  1. Lattarulo, R. 1
  2. Matute, J. A. 1
  3. J. Pérez 1
  4. Gomez Garay, V. 2
  1. 1 Tecnalia
    info

    Tecnalia

    Derio, España

  2. 2 Universidad del País Vasco/Euskal Herriko Unibertsitatea
    info

    Universidad del País Vasco/Euskal Herriko Unibertsitatea

    Lejona, España

    ROR https://ror.org/000xsnr85

Aldizkaria:
Revista iberoamericana de automática e informática industrial ( RIAI )

ISSN: 1697-7920

Argitalpen urtea: 2020

Alea: 17

Zenbakia: 1

Orrialdeak: 66-75

Mota: Artikulua

DOI: 10.4995/RIAI.2019.9542 DIALNET GOOGLE SCHOLAR lock_openSarbide irekia editor

Beste argitalpen batzuk: Revista iberoamericana de automática e informática industrial ( RIAI )

Garapen Iraunkorreko Helburuak

Laburpena

El avance logrado durante las últimas décadas en los sistemas avanzados de asistencia a la conducción (ADAS, Advanced Driver Assistance System) ha posibilitado mejorar múltiples aspectos en los vehículos comerciales, como por ejemplo la seguridad, robustez de los sistemas, eficiencia energética, detección de peatones, aparcamiento asistido y ayudas a la navegación, entre otros. Algunos desarrollos, como el control lateral y la generación óptima de trayectorias en tiempo real, están en pleno desarrollo. En este trabajo se presenta una arquitectura dual-modular cuyas principales características son su capacidad para integrar y probar nuevos algoritmos de control y decisión (modular), y la posibilidad de llevar a cabo pruebas en entornos simulados y en plataformas reales (dual), reduciendo los tiempos y costes de desarrollo. Con esta arquitectura se han podido probar diferentes técnicas de control y de generación de trayectorias, realizando además simulaciones, y comparando los resultados obtenidos con un vehículo real.

Finantzaketari buruzko informazioa

Finantzatzaile

Erreferentzia bibliografikoak

  • Alia, C., Gilles, T., Reine, T., Ali, C., Jun. 2015. Local trajectory planning and tracking of autonomous vehicles, using clothoid tentacles method. In: 2015 IEEE Intelligent Vehicles Symposium (IV). pp. 674-679. https://doi.org/10.1109/IVS.2015.7225762
  • Bagheri, M., Siekkinen, M., Nurminen, J. K., Nov. 2014. Cellular-based vehicle to pedestrian (V2p) adaptive communication for collision avoidance. In: 2014 International Conference on Connected Vehicles and Expo (ICCVE). pp. 450-456. https://doi.org/10.1109/ICCVE.2014.7297588
  • Bengler, K., Dietmayer, K., Farber, B., Maurer, M., Stiller, C., Winner, H., 2014. Three Decades of Driver Assistance Systems: Review and Future Perspectives. IEEE Intelligent Transportation Systems Magazine 6 (4), 6-22. https://doi.org/10.1109/MITS.2014.2336271
  • Berntorp, K., Hoang, T., Quirynen, R., , Cairano, S.D., 2018. Control architecture design for autonomous vehicles. Conference on Control Technology and Applications (CCTA). https://doi.org/10.1109/CCTA.2018.8511371
  • Bertoncello, M., Wee, D., 2015. Ten ways autonomous driving could redefine the automotive world | McKinsey & Company.
  • Falcone, P., Borrelli, F., Asgari, J., Tseng, H. E., Hrovat, D., May 2007. Predictive Active Steering Control for Autonomous Vehicle Systems. IEEE Transactions on Control Systems Technology 15 (3), 566-580. https://doi.org/10.1109/TCST.2007.894653
  • Favaró, F.M., Nader, N., Eurich, S.O., Tripp, M., Varadaraju, N., 2017. Examining accident reports involving autonomous vehicles in california. PLoS one 12(9). https://doi.org/10.1371/journal.pone.0184952
  • Gonzalez, D., Pérez, J., Jun. 2013. Control architecture for Cybernetic Transportation Systems in urban environments. In: 2013 IEEE Intelligent Vehicles Symposium (IV). pp. 1119-1124. https://doi.org/10.1109/IVS.2013.6629616
  • Gonzalez, D., Pérez, J., Lattarulo, R., Milanés, V., Nashashibi, F., Oct. 2014. Continuous curvature planning with obstacle avoidance capabilities in urban scenarios. In: 2014 IEEE 17th International Conference on Intelligent Transportation Systems (ITSC). IEEE, Qingdao, China. https://doi.org/10.1109/ITSC.2014.6957887
  • Gonzalez, D., Pérez, J., Milanés, V., Nashashibi, F., 2015. A review of motion planning techniques for automated vehicles. IEEE Transactions on Intelligent Transportation Systems. https://doi.org/10.1109/TITS.2015.2498841
  • Harding, J., Powell, G., Yoon, R., Fikentscher, J., Doyle, C., Sade, D., Lukuc, M., Simons, J., Wang, J., Aug. 2014. Vehicle-to-Vehicle Communications: Readiness of V2v Technology for Application. URL https://trid.trb.org/view.aspx?id=1323282
  • Hessburg, T., Tomizuka, M., Aug. 1994. Fuzzy logic control for lateral vehicle guidance. IEEE Control Systems 14 (4), 55-63. https://doi.org/10.1109/37.295971
  • Garcia de Jalon, J., Bayo, E., 1994. Kinematic and Dynamic Simulation of Multibody Systems. The Real-Time Challenge. Springer-Verlag New York. springer-verlag new york ed., Springer-Verlag New York. https://doi.org/10.1007/978-1-4612-2600-0
  • Jochem, T., Pomerleau, D., Kumar, B., Armstrong, J., 1995. PANS: a portable navigation platform. IEEE, pp. 107-112. URL http://ieeexplore.ieee.org/document/528266/
  • Jones, T., Lennox, S., Sgueglia, J., Demerly, J., Zervoglos, N.A., Yang, H.H., 2018. Autonomous vehicle: modular architecture.
  • Juez Uriagereka, G., Lattarulo, R., Perez Rastelli, J., Amparan Calonge, E., Ruiz Lopez, A., Espinoza Ortiz, H., Jun. 2017. Fault Injection method for Safety and Controllability Evaluation of Automated Driving. In: Fault Injection method for Safety and Controllability Evaluation of Automated Driving. Redondo Beach, California, pp. 1867 - 1872. https://doi.org/10.1109/IVS.2017.7995977
  • Klaus, T.C., Twitty, C.K., ERLIEN, S.M., Kegelman, J.C., Price, C.A., SCHUH, A.B., SILVERMAN, B.J., SWITKES, J.P., 2018. Automated vehicle control system architecture.
  • Kress-Gazit, H., Pappas, G. J., Aug. 2008. Automatically synthesizing a planning and control subsystem for the DARPA urban challenge. In: 2008 IEEE International Conference on Automation Science and Engineering. pp. 766-771. https://doi.org/10.1109/COASE.2008.4626549
  • Lattarulo, R., González, L., Martí, E., Matute, J., Marcano, M., Pérez, J., 2018a. Urban motion planning framework based on n-bézier curves considering comfort and safety. Journal of Advanced Transportation. https://doi.org/10.1155/2018/6060924
  • Lattarulo, R., Hess, D., Matute, J.A., Pérez, J., 2018b. Towards conformant models of automated electric vehicles. IEEE International Conference on Vehicular Electronics and Safety. https://doi.org/10.1109/ICVES.2018.8519484
  • Lattarulo, R., Hess, D., Pérez, J., 2018c. A linear model predictive planning approach for overtaking manoeuvres under possible collision circumstances. IEEE Intelligent Vehicles Symposium (IV) , 1340 - 1345. https://doi.org/10.1109/IVS.2018.8500542
  • Lattarulo, R., Martí, E., Marcano, M., Matute, J., Pérez, J., 2018d. A speed planner approach based on b'ezier curves using vehicle dynamic constrains and passengers comfort. IEEE International Symposium on Circuits and Systems (ISCAS) , 1 - 5. https://doi.org/10.1109/ISCAS.2018.8351307
  • Lattarulo, R., Perez, J., Dendaluce, M., Jul. 2017. A complete framework for developing and testing automated driving controllers. In: A complete framework for developing and testing automated driving controllers. IFAC, Toulouse, France. https://doi.org/10.1016/j.ifacol.2017.08.043
  • Lee, S. H., Lee, Y. O., Kim, B. A., Chung, C. C., Jun. 2012. Proximate model predictive control strategy for autonomous vehicle lateral control. In: 2012 American Control Conference (ACC). pp. 3605-3610.
  • Li, S., Li, K., Rajamani, R., Wang, J., May 2011. Model Predictive Multi Objective Vehicular Adaptive Cruise Control. IEEE Transactions on Control Systems Technology 19 (3), 556-566. https://doi.org/10.1109/TCST.2010.2049203
  • Marcano, M., Matute, J.A., Lattarulo, R., Martí, E., Pérez, J., 2018. Low speed longitudinal control algorithms for automated vehicles in simulation and real platforms. Hindawi Complexity. https://doi.org/10.1155/2018/7615123
  • Matute, J.A., Marcano, M., Asier Zubizarreta, J.P., 2018. Longitudinal model predictive control with comfortable speed planner. IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC). https://doi.org/10.1109/ICARSC.2018.8374161
  • Milanés, V., Onieva, E., Pérez, J., de Pedro, T., González, C., 2009. Control de Velocidad basado en Lógica Borrosa para Entornos Urbanos Congestionados. Revista Iberoamericana de Automática e Informática Industrial RIAI 6 (4), 61-68. https://doi.org/10.1016/S1697-7912(09)70109-8
  • Milanés, V., Villagra, J., Godoy, J., Simo, J., Perez, J., Onieva, E., Mar. 2012a. An Intelligent V2i-Based Traffic Management System. IEEE Transactions on Intelligent Transportation Systems 13 (1), 49-58. https://doi.org/10.1109/TITS.2011.2178839
  • Milanés, V., Villagra, J., Pérez, J., Gonzalez, C., Jan. 2012b. Low-Speed Longitudinal Controllers for Mass-Produced Cars: A Comparative Study. IEEE Transactions on Industrial Electronics 59. https://doi.org/10.1109/TIE.2011.2148673
  • Onieva, E., Milanés, V., Pérez, J., de Pedro, T., Apr. 2010. Estimación de un Control Lateral Difuso de Vehículos. Revista Iberoamericana de Automática e Informática Industrial RIAI 7 (2), 91-98. https://doi.org/10.1016/S1697-7912(10)70029-7
  • Ozguner, U., Redmill, K. A., Broggi, A., Jun. 2004. Team TerraMax and the DARPA grand challenge: a general overview. In: IEEE Intelligent Vehicles Symposium, 2004. pp. 232-237.
  • Pacejka, H. B., 2006. Tire and Vehicle Dynamics. In: Pacejka, H. B. (Ed.), Tire and Vehicle Dynamics, 2nd Edition. Butterworth-Heinemann, Oxford, p. 642.
  • Perez, J., Milanes, V., Onieva, E., Mar. 2011. Cascade Architecture for Lateral Control in Autonomous Vehicles. IEEE Transactions on Intelligent Transportation Systems 12 (1), 73-82. https://doi.org/10.1109/TITS.2010.2060722
  • Perez, J., Milanes, V., Onieva, E., Godoy, J., Alonso, J., Apr. 2011. Longitudinal fuzzy control for autonomous overtaking. In: 2011 IEEE International Conference on Mechatronics. pp. 188-193. https://doi.org/10.1109/ICMECH.2011.5971279
  • Perez, J., Nashashibi, F., Lefaudeux, B., Resende, P., Pollard, E., Feb. 2013. Autonomous Docking Based on Infrared System for Electric Vehicle Charging in Urban Areas. Sensors (Basel, Switzerland) 13 (2), 2645-2663. https://doi.org/10.3390/s130202645
  • Pérez R., J., Lattarulo, R., Nashashibi, F., 2014. Dynamic trajectory generation using continuous-curvature algorithms for door to door assistance vehicles, in: 2014 IEEE Intelligent Vehicles Symposium Proceedings, pp. 510-515.
  • Tas, Ö.S., Hörmann, S., Schaüfele, B., Kuhnt, F., 2018. Automated vehicle system architecture with performance assessment. IEEE International Conference on Intelligent Transportation Systems . https://doi.org/10.1109/ITSC.2017.8317862
  • The International Traffic Safety Data and Analysis Group IRTAD, 2017. IRTAD: Road Safety Annual Report 2016. URL: https://www.itf-oecd.org/road-safety-annual-report-2016.
  • Thrun, S., 2006. Winning the DARPA Grand Challenge: A Robot Race through the Mojave Desert. In: 21st IEEE/ACM International Conference on Automated Software Engineering (ASE'06). https://doi.org/10.1109/ASE.2006.74
  • Villagra, J., Milanes, V., Perez, J., de Pedro, T., Oct. 2010. Control basado en PID inteligentes: aplicación al control de crucero de un vehículo a bajas velocidades. Revista Iberoamericana de Automática e Informática Industrial RIAI 7 (4), 44-52. https://doi.org/10.1016/S1697-7912(10)70059-5
  • Woo, H. J., Park, S. B., Kim, J. H., Oct. 2008. Research of the optimal path planning methods for unmanned ground vehicle in DARPA Urban Challenge. In: 2008 International Conference on Control, Automation and Systems. pp. 586-589.
  • Yoon, J., Crane, C. D., Oct. 2008. LADAR based obstacle detection in an urban environment and its application in the DARPA Urban challenge. In: 2008 International Conference on Control, Automation and Systems. pp. 581-585. https://doi.org/10.1109/ICCAS.2008.4694569