###### Abstract
The GNSS PVT information is comprised of National Marine Electronics Association (NMEA) messages, and the target vehicle parses the incoming NMEA sentences in a serial manner [14]. With the aid of a multi-attribute decision-making (MADM) module, the target vehicle optimally decides in real-time which neighbors to select for retrieving the GNSS corrections for improving/updating its own PVT state. The contributions of this work are summarized as follows:  
* A CP solution stemming from the C-DGNSS concept is proposed to enhance the performance of low-cost GNSS receivers in safety-critical ITS scenarios. The target's vehicle receiver can obtain GNSS corrections from a neighboring vehicle and update its own position in real-time;
* The proposed C-DGNSS methodology is aided by a MADM module that, given a variety of position-related criteria and alternative neighboring vehicles, ranks them and optimally decides which neighbor to select to retrieve PVT corrections. * Real experimental measurements from several low-cost GNSS receivers and trajectories (experimental sessions) are provided to simulate various operating environments (i.e., deep urban, suburban, and rural areas);
* The experimental data are easily processed NMEA sentences which are manufactured universally regardless of GNSS receiver producer. The globally available NMEA data formats are fed as input (i.e., criteria values) to the considered MADM algorithms;
* Thirteen MADM algorithms are simulated with various weightings, normalization techniques, and criteria associated with positioning accuracy and reliability, such as horizontal accuracy, dilution of precision (DOP), integer ambiguity status, etc. ;
* A comparative analysis is provided through an evaluation of the MADM algorithms in terms of ranking performance and robustness. An investigation of the importance and criticality of the criteria is also presented (sensitivity analysis) together with the necessary simulations' ranking results and MADM algorithms' performance tables;
* The proposed C-DGNSS algorithm will be beneficial for critical applications such as anti-collision, lane-keeping, and intersection crossing, which require high relative positioning accuracy. Moreover, it aims to improve the positioning accuracy of low-cost receivers in complex propagation environments by minimizing the operational overheads but does not guarantee the effective minimization and elimination of user-related errors;
* The multi-purpose, generic applicability of the proposed scheme is not only for land vehicles but extends to drone positioning, swarm-of-entities guidance, drone-to-car communication, etc. The remainder of the paper is structured as follows: in Section 2, a brief review of the ITS definitions and usages is reported, and a summary of the C-DGNSS framework on the enhancement of low-cost GNSS receivers is presented, along with the specifications for ITS positioning quality. In Section 3, the MADM theory is developed, and the employed MADM algorithms, normalization techniques, and weightings are elaborated. In Section 4, the simulation environment (trajectory, alternative vehicles, and input parameters) is described, and the MADM simulations using the experimental data take place. The ranking and numerical results are exhibited, and comments are made. Finally, Section 5 concludes the paper.