# Effects of Vehicular Communication on Risk Assessment in Automated Driving Vehicles
## 2 Sensor Characteristics and Information Fusion
### On-board Ranging Sensors  
The radar is currently the most widely adopted sensing technology for automotive ranging applications. The radio detection and ranging (RADAR) is a system that uses electromagnetic waves to identify the range, direction, or speed of both moving and fixed objects such as aircraft, ships, motor vehicles, weather formations, and terrain. In this technology, the distance from the object is calculated through the echoes that are sent back from the object. The determination of the position of an object is done through the time-of-flight and angle measurement. In process of time-of-flight measurements, electromagnetic energy is sent toward objects and the returning echoes are observed. The measured time difference and the speed of the signal allow calculating the distance to the object. The Speed measurement is made through the Doppler effect. The base of the Doppler effect is change of wavelength due to the changing gap between waves. Although the amount of signal returned is tiny, radio signals can easily be detected and amplified. RADAR sensors are also known to have sufficient robustness to function reliably under harsh environmental conditions for extended periods of time [12]. Vision sensor systems use one or several cameras together with a microprocessor to perform image processing. Since they operate in the visible light region, their capabilities are similar to that of our own eyes. A camera-based sensor is used to detect car/obstacle in front of the subject vehicle. Camera-based longitudinal safety systems are typically used for medium range, medium field of view detection. The camera system can be charge coupled device (CCD)-based or Complementary Metal Oxide Semiconductor (CMOS)-based [13]. In their basic single camera configuration, video imagers struggle to provide ranging information. However, using the principle of triangulation coupled to obstacle recognition routines, the images viewed by camera systems may be processed to facilitate identification of obstacles and their range. Such systems provide good obstacle and environmental recognition using non-intrusive means. Cameras are able to provide information about target position for slow moving vehicles. They are capable of detecting targets even when placed at a distance from the region to be monitored. However, cameras placed in this fashion provide poor longitudinal position accuracy. An experiment was performed by using the test vehicle which is equipped with radar and vision sensor systems for measuring the range and range-rate to the proceeding vehicle under vehicle following situation in order to evaluate longitudinal safety. Data acquisition is performed at various ranges and relative velocities with constant speed of the target vehicle. In many cases, due to road curvatures, other vehicles, uneven road surfaces relative lateral position and lateral movement, the measurement range distribution might be different. Also, the exact reflection point is uncertain since the azimuth angle is not very exact, so for medium distances the main reflection point may be located on different parts of the car. Hence, test data was collected in the test road without other vehicle or obstacle. The lateral displacement of the longitudinal centerline of the subject vehicle relative to the longitudinal centerline of the target vehicle kept less than 0 m. The subject vehicle cruises behind the preceding vehicles in initial vehicle speed. The initial speed and range of subject vehicle (SV) and preceding vehicle (PV) are set to be Table 1. To validate the sensor detection performance, the GPS-based device, RT-Range, is used to measure the reference of the range and range rate data. The RT-Range device uses RT-3000 which is precision GPS device, and is equipped on the test vehicle respectively. In Figure 1, range error in vehicle test is depicted. As shown in Figure 1, vision sensor and radar sensor have similar detection error pattern within the 10 m range. On the other hand, range error in vehicle test is depicted.