Tetiana Zinchenko

Vehicle-to-Vehicle IEEE 802.11p performance measurements at urban intersections

During the last few years, vehicle-to-vehicle (V2V) wireless communication has become a key objective for enabling future cooperative safety applications, such as intersection collision warning. In this paper, we present the results of a 5.9 GHz V2V performance measurement campaign at four different urban intersections under NLOS conditions using commercial off-the-shelf wireless interface cards which meet the 802.11p and ITS-G5 specifications. Particularly, we quantify the packet delivery ratio (PDR) and received signal strength indication (RSSI) levels associated with different scenario conditions with respect to vehicle positioning, intersection geometry and traffic density. We determine reliable communication ranges which constitute an important metric for V2V collision avoidance applications.

Impact of buildings on vehicle-to-vehicle communication at urban intersections

Although the potential of Vehicular Ad-Hoc Networks (VANETS) to improve road safety and traffic efficiency for next-generation vehicular traffic system has been well investigated and proved, the performance of vehicle-to-vehicle (V2V) communication, especially at urban intersections has not been clearly quantified. In this paper, we evaluate the effects of buildings on the vehicle-to-vehicle performance at urban intersections based on a profound simulation campaign. Due to the two-dimensional nature of intersection topologies, we investigate the performance of V2V communication by analyzing packet delivery ratios and packet drop rates with respect to sender and receivers position under varying node density and intersection layout. While stationary and mobile obstacles considerably attenuate the received signal power, the results reveal that the presence of buildings could in some situations improve the performance of V2V communication by reducing co-channel interference from hidden nodes.

Effects of Vegetation on Vehicle-to-Vehicle Communication Performance at Intersections

Vehicle-to-Vehicle (V2V) communication is envisioned to enable a vast range of road safety, traffic efficiency and infotainment applications for next-generation vehicular traffic. In this paper, we investigate the effects of vegetation on the performance of V2V communication based on a 5.9GHz measurement campaign conducted at different urban and rural intersections with different types of vegetation under non-line-of-sight (NLOS) conditions. We evaluate received power levels and packet delivery rates under varying conditions with respect to vehicle positioning, intersection layout and vegetation type. To capture the additional signal attenuation caused by foliage, the measurements for each intersection were conducted both in summer and in winter, which allows comparing the impact of leaved and leafless vegetation. Moreover, we derive the additional attenuation caused by vegetation and compare the measurement results with three well-known empirical models for vegetation-induced path loss. Based on the acquired sets of measurement data, we present a simple parametrized model for estimation of path loss caused by vegetation in V2V scenarios.

Reliability analysis of vehicle-to-vehicle applications based on real world measurements

Safety applications are envisioned to be the first Vehicle-to-Vehicle (V2V) applications delivered to the mass market in the near future. In this paper, we address the question of achievable application-level reliability while operating over the Dedicated Short Range Communication (DSRC) channel. We advocate, that this reliability is a cumulative metric, which combines the main application operational requirements bounded with network performance metrics. In this context, we focus on (i) required information freshness and communication range, as main communication performance requirements and (ii) path prediction error, as application operational requirement. We present a novel simulation approach towards quantifying these metrics based on MATLAB vehicle dynamics models coupled with a driver reaction model. The input data for the simulation study is obtained empirically through real world experiments. This allows us to achieve numerical results with high accuracy. Further, based on data gathered in extensive real world measurement campaigns, we assess application-level reliability under different realistic conditions and perform a feasibility analysis of various NLOS scenarios while showing their potential for future V2V applications on the example of the Intersection Collision Warning (ICW). Finally, we investigate whether the packet delivery ratio (PDR) is capable to capture application-level reliability adequately and compare it with the metrics proposed in this work.

Real-time prediction of communication link quality for V2V applications

In this paper we address prediction of the communication link quality for Vehicle-to-Vehicle (V2V) applications. We focus on the prediction at the receiver vehicle and suggest two novel frameworks, which allow real-time and short-term prediction whether a predefined application-specific QoS will be maintained in the near future. First framework makes use of machine learning approach, and the second one is realized with model-based estimation. Both frameworks are developed based on the measurement data which was gathered over the 5,5 month of the field trials in the simTD project. In our paper we also suggest an optimization method to increase prediction accuracy and validate both frameworks through an additional real-world measurement campaign. The main advantages of suggested algorithms comparing to the existing work is their completely generic nature and low to no memory requirements. We demonstrate that in low network density scenarios prediction accuracy can reach up to 97%.