Positioning in road network environment requires a process with which can be able to match the raw coordinates, obtained from the positioning sensor(s), to the links of the network. Such matching process is necessary for two obvious reasons. First, positional data is not definite, and second, map coordinates are not absolute. Hence, there is a need for a process, known as map-matching, to reconcile two groups of coordinates. Accordingly, to provide some location-based services in network areas, performing a map-matching process seems inevitable. In this paper, after discussing several types of geometric map-matching methods, which is the most basic form of map-matching, a weighted-base map-matching algorithm is developed.The participating parameters’ weights are optimized experimentally. The algorithm takes three parameters as input: ‘Distance’, ‘Heading Convergency’, and ‘Relational Position’. Four types of modelling for ‘Relational Position’ are presented. The most effective type is then recognized after executing tests on algorithm performance. Also, comparing the performance of the suggested map-matching algorithm to the map-matching algorithms of the same complexity developed in other studies shows that the suggested algorithm is more efficient. This paper's suggested algorithm provided 95.5 percent of true link selection during the performance assessment.