A Research Platform for Autonomous Vehicles Technologies Research in the Insurance Sector
Source abstract
Abstract
This work presents a novel platform for autonomous vehicle technologies research for the insurance sector. The platform has been collaboratively developed by the insurance company MAPFRE-CESVIMAP, Universidad Carlos III de Madrid and INSIA of the Universidad Politécnica de Madrid. The high-level architecture and several autonomous vehicle technologies developed using the framework of this collaboration are introduced and described in this work. Computer vision technologies for environment perception, V2X communication capabilities, enhanced localization, human–machine interaction and self awareness are among the technologies which have been developed and tested. Some use cases that validate the technologies presented in the platform are also presented; these use cases include public demonstrations, tests of the technologies and international competitions for self-driving technologies.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Autonomous Vehicle Technology and Safety · Robotic Path Planning Algorithms · Robotics and Sensor-Based Localization
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Intelligent Systems Lab (LSI) Research Group, Universidad Carlos III de Madrid (UC3M), 28911 Leganés, Spain
Departamento de Movilidad, CESVIMAP-MAPFRE, 05004 Ávila, Spain
Funding
Ministerio de Ciencia y Tecnología · Comunidad de Madrid · Comunidad de Madrid through the Universidad Carlos III de Madrid
References (27)
Show source-provided references
1. A Review of Sensor Technologies for Perception in Automated Driving10.1109/MITS.2019.2907630 ↗
2. Experience, Results and Lessons Learned from Automated Driving on Germany’s Highways10.1109/MITS.2014.2360306 ↗
3. Making Bertha Drive—An Autonomous Journey on a Historic Route10.1109/MITS.2014.2306552 ↗
4. Ros-based architecture for autonomous intelligent campus automobile (icab)
5. De Miguel, M.Á., Moreno, F.M., García, F., Armingol, J.M., and Martin, R.E. (2019). Autonomous vehicle architecture for high automation. International Conference on Computer Aided Systems Theory, Springer.
6. Guindel, C., Beltrán, J., Martín, D., and García, F. (2017, January 16–19). Automatic extrinsic calibration for lidar-stereo vehicle sensor setups. Proceedings of the Intelligent Transportation Systems (ITSC), Yokohama, Japan.10.1109/ITSC.2017.8317829 ↗
7. LOAM: Lidar Odometry and Mapping in Real-time
8. De Miguel, M.Á., García, F., and Armingol, J.M. (2020). Improved LiDAR Probabilistic Localization for Autonomous Vehicles Using GNSS. Sensors, 20.10.3390/s20113145 ↗
9. Osman, M., Alonso, R., Hammam, A., Moreno, F.M., Al-Kaff, A., and Hussein, A. (2019, January 9–12). Multisensor Fusion Localization using Extended Hinf Filter using Pre-filtered Sensors Measurements. Proceedings of the 2019 IEEE Intelligent Vehicles Symposium (IV), Paris, France.10.1109/IVS.2019.8814234 ↗
10. Ismail, M., Tarek, A., Plaza, P.M., Gomez, D.M., Armingol, J.M., and Abdelaziz, M. (2019, January 4–6). Advanced Mapping and Localization for Autonomous Vehicles using OSM. Proceedings of the 2019 IEEE International Conference of Vehicular Electronics and Safety (ICVES), Cairo, Egypt.10.1109/ICVES.2019.8906306 ↗
11. Moreno, F.M., El-Sobky, O., Garcia, F., and Armingol, J.M. (2019, January 4–6). Hypergrid: A Hyper-Fast ROS-Based Framework for Local Map Generation. Proceedings of the 2019 IEEE International Conference on Vehicular Electronics and Safety (ICVES), Cairo, Egypt.10.1109/ICVES.2019.8906334 ↗
12. Fast Joint Object Detection and Viewpoint Estimation for Traffic Scene Understanding10.1109/MITS.2018.2867526 ↗
13. Beltran, J., Guindel, C., Moreno, F.M., Cruzado, D., Garcia, F., and de la Escalera, A. (2018). BirdNet: A 3D Object Detection Framework from LiDAR information. arXiv.10.1109/ITSC.2018.8569311 ↗
14. Barrera, A., Guindel, C., Beltrán, J., and García, F. (2020). BirdNet+: End-to-End 3D Object Detection in LiDAR Bird’s Eye View. arXiv.10.1109/ITSC45102.2020.9294293 ↗
15. Barrera, A., Guindel, C., García, F., and Martín, D. (2018, January 5–7). Análisis, evaluación e implementación de algoritmos de segmentación semántica para su aplicación en vehículos inteligentes. Proceedings of the Actas de las XXXIX Jornadas de Automática, Badajoz, Spain.
16. Bianco, L.C.L., Al-Kaff, A., Beltrán, J., Fernández, F.G., and López, G.F. (2019). Joint Instance Segmentation of Obstacles and Lanes Using Convolutional Neural Networks. Iberian Robotics Conference, Springer.
17. Wang, J., Chi, W., Li, C., Wang, C., and Meng, M.Q. (2020). Neural RRT*: Learning-Based Optimal Path Planning. IEEE Trans. Autom. Sci. Eng., 1–11.10.1109/TASE.2020.2976560 ↗
18. Wang, J., Meng, M.Q., and Khatib, O. (2020). EB-RRT: Optimal Motion Planning for Mobile Robots. IEEE Trans. Autom. Sci. Eng., 1–11.10.1109/TASE.2020.2987397 ↗
19. Werling, M., Ziegler, J., Kammel, S., and Thrun, S. (2010, January 3–7). Optimal trajectory generation for dynamic street scenarios in a frenet frame. Proceedings of the 2010 IEEE International Conference on Robotics and Automation, Anchorage, AK, USA.10.1109/ROBOT.2010.5509799 ↗
20. Hoffmann, G.M., Tomlin, C.J., Montemerlo, M., and Thrun, S. (2007, January 9–13). Autonomous automobile trajectory tracking for off-road driving: Controller design, experimental validation and racing. Proceedings of the 2007 American Control Conference, New York, NY, USA.10.1109/ACC.2007.4282788 ↗
21. Kokuti, A., Hussein, A., Marín-Plaza, P., de la Escalera, A., and García, F. (2017, January 27–28). V2X communications architecture for off-road autonomous vehicles. Proceedings of the 2017 IEEE International Conference on Vehicular Electronics and Safety (ICVES), Vienna, Austria.10.1109/ICVES.2017.7991903 ↗
22. Hussein, A., García, F., Armingol, J.M., and Olaverri-Monreal, C. (2016, January 1–4). P2V and V2P communication for Pedestrian warning on the basis of Autonomous Vehicles. Proceedings of the 2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC), Rio de Janeiro, Brazil.10.1109/ITSC.2016.7795885 ↗
23. Alvarez, W.M., Moreno, F.M., Sipele, O., Smirnov, N., and Olaverri-Monreal, C. (2020). Autonomous Driving: Framework for Pedestrian Intention Estimationin a Real World Scenario. arXiv.10.1109/IV47402.2020.9304624 ↗
24. Dosovitskiy, A., Ros, G., Codevilla, F., Lopez, A., and Koltun, V. (2017). CARLA: An Open Urban Driving Simulator. arXiv.
25. Krajzewicz, D., Hertkorn, G., Feld, C., and Wagner, P. (2002). SUMO (Simulation of Urban MObility)—An open-source traffic simulation. Proceedings of the 4th Middle East Symposium on Simulation and Modelling (MESM20002), SCS Europe.
26. de Miguel, M.Á., Fuchshuber, D., Hussein, A., and Olaverri-Monreal, C. (2019, January 9–12). Perceived Pedestrian Safety: Public Interaction with Driverless Vehicles. Proceedings of the2019 IEEE Intelligent Vehicles Symposium (IV), Paris, France.10.1109/IVS.2019.8814145 ↗
27. Alvarez, W.M., de Miguel, M.Á., García, F., and Olaverri-Monreal, C. (2019, January 27–30). Response of Vulnerable Road Users to Visual Information from Autonomous Vehicles in Shared Spaces. Proceedings of the 2019 IEEE Intelligent Transportation Systems Conference (ITSC), Auckland, New Zealand.10.1109/ITSC.2019.8917501 ↗