This paper explores the potentialities of deploying vehicular Cooperative Positioning (CP) systems in urban scenarios utilizing real-world data collected via experimental campaigns. We examine the case of two prototype vehicles equipped with LiDAR sensors for perceiving their surrounding environment and with Global Navigation Satellite System (GNSS) receivers for positioning. The considered use case focuses on the cooperative detection of static landmarks, to be used for improving the vehicles’ GNSS positioning. The experimental campaign points out a severe degradation in ego vehicle localization performances due to complex multipath propagation experienced in the urban scenario. To cope with such a problem, we integrate into the CP system a compensation method able to mitigate the position bias originating from the adverse propagating conditions. Experimental results show that integrating the developed compensation into the CP solution enables an accurate detection of the landmark positions, leading to an enhancement of the vehicle localization accuracy.