###### Abstract  
Satellite positioning lies within the very core of numerous Intelligent Transportation Systems (ITS) and Future Internet applications. With the emergence of connected vehicles, the performance requirements of Global Navigation Satellite Systems (GNSS) are constantly pushed to their limits. To this end, Cooperative Positioning (CP) solutions have attracted attention in order to enhance the accuracy and reliability of low-cost GNSS receivers, especially in complex propagation environments. In this paper, the problem of efficient and robust CP employing low-cost GNSS receivers is investigated over critical ITS scenarios. By adopting a Cooperative-Differential GNSS (C-DGNSS) framework, the target's vehicle receiver can obtain Position-Velocity-Time (PVT) corrections from a neighboring vehicle and update its own position in real-time. A ranking module based on multi-attribute decision-making (MADM) algorithms is proposed for the neighboring vehicle rating and optimal selection. The considered MADM techniques are simulated with various weightings, normalization techniques, and criteria associated with positioning accuracy and reliability. The obtained criteria values are experimental GNSS measurements from several low-cost receivers. A comparative and sensitivity analysis are provided by evaluating the MADM algorithms in terms of ranking performance and robustness. The positioning data time series and the numerical results are then presented, and comments are made. Scoring-based and distance-based MADM methods perform better, while L1 RMS, HDOP, and Hz std are the most critical criteria. The multi-purpose applicability of the proposed scheme, not only for land vehicles, is also discussed. Intelligent Transportation Systems; Cooperative Positioning; low-cost GNSS; connected vehicles; multi-criteria decision making; ranking methods; sensitivity analysis +
Footnote †: journal: Future Internet  
Interruptions of satellite positioning regarding signal receptions in obstructed skies and complex propagation environments will require coupling with communication technologies and other sensors for more demanding applications [10; 11]. Fusion with other onboard sensors, such as inertial sensors, lidars, ultra-wideband, and cameras, will be inevitable for both categories in order to fulfill the requirements of the applications [10; 11]. However, Inertial Navigation System (INS)/GNSS integration can come at a prohibitive cost for mass deployment, has limited sensory coverage, and is unsuitable for small hand-held devices. Similarly, Real-time Kinematic Positioning (RTK) constitutes a Differential GNSS (D-GNSS) technique to improve the positioning accuracy of the receiver but does not provide a stable solution in deep urban centers [12]. Communication technologies empower vehicle-to-everything (V2X) information share, and as they are established in the vehicle industry, a wide range of ITS applications emerge [13]. Hence, V2X and C-ITS are paving the way for Cooperative Positioning (CP) among mobile terminals but demand the highest performance levels for several metrics such as availability, accuracy, robustness, and integrity [13]. In this work, the challenge of efficient, accurate, and reliable CP that incorporates low-cost GNSS receivers in various critical ITS scenarios was addressed. The Cooperative Differential GNSS (C-DGNSS) framework was employed, which is the classical D-GNSS coupled with CP between a target vehicle and a number of surrounding candidate neighbors. All of the cars are considered connected. That means that data can be exchanged through all the vehicles and belong to a wireless network. By retaining the properties of D-GNSS, the cooperating vehicles disseminate their Position-Velocity-Time (PVT) data through radio links and GNSS corrections from the available satellites in view. The main hypothesis is that the target vehicle's low-cost receiver could improve both its relative and absolute positioning accuracy.