# Survey on Ranging Sensors and Cooperative Techniques for Relative Positioning of Vehicles
## 4 Cooperative Relative Positioning
### V2V Communication Performance  
The presented cooperative approaches are based on the exchange of position, velocity and orientation information between the vehicles. This exchange is performed by using V2V communication. The current standard for direct wireless inter-vehicle communication in the U.S. and Europe is based on the IEEE 802.11 standard working in the 5.9 GHz band. Further details on this communication technology can be found in the corresponding standards, [109; 110], and in the survey papers [111; 112; 113].  
Under ideal line-of-sight conditions, communication between vehicles above 1 km is possible with this technology [114; 115]. However, in real-world environments, adverse radio-frequency propagation conditions, including shadowing, blockage, multipath propagation and high vehicle dynamics, causing large- and small-scale fading, will make it difficult to achieve the message update rate required by the safety application. Many research groups have investigated the radio propagation channel in vehicular environments [116; 117; 118; 119]. Other research groups look into the impact in terms of the attenuation of certain obstacles, such as large vehicles on the V2V signal [120; 121]. The overall communication performance in terms of packet error rate and effective communication range is the object of research in [114; 122; 123]. According to [PERSON] et al., on average, an effective V2V communication range up to 400 m can be achieved in highway environments, while only a 100 m reliable communication range can be expected in urban scenarios [123].  
Additionally, the radio channel is shared among different traffic participants. Carrier Sense Multiple Access with Collision Avoidance (CSMA-CA) is a random contention protocol that makes it  
Figure 4: The figures show the uncertainty in the relative position of a vehicle driving 30 m (blue) and 50 m (red) ahead. The red and blue dots are the particle clouds, and the black ellipses are the linearized Gaussian uncertainty. Figure (**a**) shows the relative position in the navigation frame coordinates with a 0.5 m (1\(\sigma\)) error in the north and east direction. After rotating this position into the ego vehicle frame using the ego vehicle’s heading angle with an uncertainty of 1\({}^{\circ}\) (1\(\sigma\)) in Figure (**b**) and 5\({}^{\circ}\) (1\(\sigma\)) in Figure (**c**), the uncertainty in the relative position is clearly increased.  
possible for different nodes to communicate over a shared medium while minimizing the number of packet collisions. However, in high-traffic scenarios with high communication load, the number of packet collisions increases dramatically [124; 125].  
The challenges for both the physical propagation conditions and the medium-access technology are the cause for an unreliable information exchange between the vehicles, which leads to a decreased awareness of the ego vehicle regarding the relative position of surrounding vehicles. A suitable metric for this awareness is the update delay [126] or packet inter-reception time [127], which measures the probability of experiencing a communication outage from a certain transmitter longer than a given time. During such communication outages the relative position of a target vehicle has to be predicted, increasing the uncertainty and the risk in the case of a sudden event, such as harsh braking or a strong change in direction.