The profound knowledge of wireless propagation is essential for wireless communication between vehicles. To evolve and test communication standards we need channel models in representative environments to neither over-, nor underestimate the effect of the surrounding environment and the movement of the vehicles; typical environments for railway communication are railway station, open field and hilly environments. We introduce train-to-train (T2T) path loss models and large scale fading statistics based on channel sounder measurement data as a first step towards a geometry-based stochastic channel model (GSCM). The models represent the mentioned typical environments for railway applications. We compare the results with previous published intelligent transportation system (ITS-G5) measurement based models and highlight the differences.

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Thousands of fatalities among pedestrians are caused every year by traffic accidents. Vehicle-to-pedestrian (V2P) communication promises to prevent accidents by enabling collision avoidance application. To develop and test a V2P communications system, accurate knowledge of the propagation channel is essential. However, only limited analysis of V2P channel have been reported in the literature. To fill this gap, the German Aerospace Center conducted an extensive channel sounding measurements campaign in a controlled environment. The measurements were performed at 5.2 GHz with a bandwidth of 120 MHz. In parallel to the channel sounding measurements, performance measurements were carried out using ITS-G5 system at 5.9 GHz and with a bandwidth of 10 MHz. This paper describes the setup and the scenarios for the two measurements. First results on channel evaluation in different scenarios as well as path loss models are presented.

Vehicle-to-Vehicle (V2V) communication can significantly enhance the performance of collision avoidance systems through periodically exchanging information between vehicles. At urban intersections, the effect of shadowing caused by buildings has a severe influence on the communication performance. In addition, an increased traffic density near an intersection creates a high level of interference, which can lead to a communication performance degradation. In this paper, we evaluate the performance of IEEE 802.11p based V2V communication for cooperative collision avoidance at urban intersections. We focus on the impact of shadowing from buildings and of traffic density on the communication performance. For this purpose, we investigate the effect of both the data rate and transmission power in different scenarios. The simulation results show that transmission power and data rate can be tailored to increase the reliability of the communication for the collision avoidance system. Simulation results also show that buildings at intersections reduce the interference from vehicles in other road sections. In addition, our simulation results reveal more insight on the main cause of packet loss near intersections. They show that loss due to packet collisions is the dominant reason, which can be reduced by increasing the data rate.

Vehicle-to-vulnerable road user (V2VRU) communications have the ability to provide 360 degrees of awareness to both vehicles and vulnerable road users (VRUs) to prevent accidents. An accurate V2VRU channel model in critical accident scenarios is essential to develop a reliable communications system. Therefore, extensive wideband single-input and single-output (SISO) channel measurement campaigns at 5.2 GHz were carried out in open-field and urban environments. Accident prone scenarios between a vehicle and a cyclist as well as between a vehicle and a pedestrian are considered. In this paper, locations of the scatterers in the propagation environment are estimated. We propose a method to extract specular MPCs from the estimated timevariant channel impulse response (CIR) based on the density of neighboring MPCs. The specular MPCs are then tracked using a novel tracking algorithm based on the multipath component distance (MCD) approach. Each path is then related to a physical scatterer in the propagation environment by employing a joint delay-Doppler estimation. According to the results, single and double bounce reflections from buildings and parked vehicles are identified in line-of-sight (LoS) situation. In non-LoS (NLoS) situation, scattering from nearby trees as well as reflections from traffic signs and lampposts beneath the trees canopy are identified.

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