# A Research Platform for Autonomous Vehicles Technologies Research in the Insurance Sector
## 2 Hardware Architecture
### Sensors  
The sensor setup of an autonomous vehicle is, perhaps, the most critical aspect of the design. This is mainly due to the significant cost and to the fact that sensors are essential for autonomous driving. The configuration must include the minimum number of sensors to make sure that all elements surrounding the vehicle are correctly perceived, that it is completely secure and that it follows all driving rules. A review of different sensors and configurations for perception tasks in autonomous driving can be found in [1]. Based on previous experience, and after analyzing the behavior of different sensor setups in a simulated environment, the most adequate set of sensors that provides sufficient information about the environment consists of the following:  
**LiDAR**: The proposed sensor setup includes three light detection and ranging (LiDAR) sensors. One 32-layer LiDAR is used as the main sensor, and two 16-layer sensors are used to cover blind spots and to complement the information provided by the main LiDAR. The purpose of these sensors is twofold: on the one hand, the accuracy of the distance estimation of LiDAR sensors is remarkable for localization purposes, as detailed in Section 3.3; on the other hand, these sensors are also used for obstacle detection and localization, directly providing the 3D pose of the different objects in the scene. The selection of this set provides full 360\({}^{\circ}\)coverage without compromising the computational load.  
**Monocular camera**: Three monocular cameras are equipped and installed on the roof of the car, with an optical horizontal field of view of 90\({}^{\circ}\). This camera covers most of the front area of the vehicle and provides color images that are used later for obstacle classification (e.g., pedestrian, car, bike, etc.) and to obtain an insightful analysis of the road environment, including road lane topology, traffic signs, etc.  
**RTK GNSS and IMU**: In order to obtain the precise localization of the vehicle, a GNSS with RTK corrections, fused with an inertial measurement unit (IMU) sensor, is used based on Pix Hawk technology. This system generates precise coordinates and the orientation of the vehicle.  
**Vehicle sensors**: In addition to the extra sensors installed, the data available in the CAN bus from the vehicle sensors are also integrated, such as the wheel odometers and the steering angle sensors.  
Besides the sensor selection, it is also of great importance to determine the physical location of each sensor on the vehicle. Since this is a research platform, it is common to modify the position of the sensors, as well as to add new ones to perform experiments. For this reason, we have installed a metal rack on top of the roof where sensors can be easily installed using screws. On this rack, the monocular camera is positioned in the center of the front bar providing 189 degrees vision, so they have no occlusions from any other sensor, or from other parts of the vehicle. Then, the main LiDAR is installed at the center, with a small structure that provides an extra elevation from the roof and the rack. Regarding the two complementary 16 layer LiDARs, they are positioned at the left/right of the other LiDAR, but with a lower elevation and an extra inclination angle that allows them to cover the blind areas of the main LiDAR. Finally, the GNSS and IMU units are positioned at the back of the rack. Last, but not least, in order to combine and fuse the information received from each sensor, we need to know the relative position and orientation between them with a very high accuracy. Using the algorithm presented in [6], it is possible to perform an automatic calibration of these extrinsic parameters for LiDAR and camera sensors with a high accuracy.