Line-of-Sight Obstruction Analysis for Vehicle-to-Vehicle Network Simulations in a Two-Lane Highway Scenario

Abbas, Taimoor; Tufvesson, Fredrik · 2013 · Crossref

DOI: 10.1155/2013/459323

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Summary

This paper addresses the critical issue of line-of-sight (LOS) obstruction by neighboring vehicles in vehicle-to-vehicle (V2V) communication networks, a factor often neglected in existing vehicular ad-hoc network (VANET) simulations. The authors highlight that obstructing vehicles can introduce 10–20 dB of additional path loss, significantly reducing communication range. To address this gap, the study proposes a Traffic Mobility Model (TMM) capable of identifying whether vehicles are in LOS or obstructed-line-of-sight (OLOS) states, enabling more realistic simulation of packet reception probabilities. The methodology employs a car-following model with lane-changing capabilities to simulate traffic flow on a two-lane highway. Implemented in MATLAB, the model uses optimal velocity functions and specific lane-change criteria based on safety distances and incentives to determine vehicle positions and movements. The simulation setup involves a 14.4 km circular highway with realistic traffic densities and speeds (e.g., 100 km/h in the outer lane, 70 km/h in the inner lane). The TMM categorizes vehicles relative to a transmitter (TX) by modeling vehicles as geometric screens; vehicles within a defined communication radius are classified as LOS if unobstructed, or OLOS if shadowed by other vehicles. The model logs instantaneous positions, headways, and state transitions over a 3-hour simulation period. Key findings demonstrate that the proposed TMM effectively captures realistic traffic dynamics, including significant variations in headway distances (ranging from 20 to 600 meters) and diverse lane-changing behaviors. The analysis reveals the probabilities of vehicles being in LOS or OLOS states as a function of distance from the TX. Specifically, the study calculates state transition intensities for LOS-to-OLOS and OLOS-to-LOS transitions, yielding values of 0.0035 m⁻¹ and 0.0020 m⁻¹, respectively. These simulated intensities closely match mean values derived from independent measurement campaigns, validating the model's accuracy. Furthermore, cumulative distribution functions illustrate the distribution of vehicles in LOS and OLOS states within the communication range and the distances traveled in each state. The significance of this work lies in providing a straightforward, low-complexity TMM that can be integrated into VANET simulators to account for LOS obstruction. By distinguishing between LOS and OLOS scenarios, the model allows for more accurate analytical estimations of packet reception probabilities using various channel models. This contribution enhances the realism of V2V network simulations, particularly for safety-critical applications where accurate modeling of signal attenuation due to vehicle obstruction is essential. The study confirms that incorporating such geometric obstruction analysis is vital for evaluating the performance of future intelligent transportation systems.

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• v2x connected vehicle