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The latency requirements of delay-sensitive applications such as cooperative, connected, and automated mobility (CCAM) services challenge the capabilities of traditional vehicular radio access technologies (i.e., IEEE 802.11P and cellular networks). To this end, the 5G cellular network is adopting the multi-access edge computing (MEC) paradigm. However, the use of this technology comes with several challenges. In this article, MEC placement challenges and their impact on network deployment costs are studied. We propose three MEC clustering models and compare them from a cost perspective. Results show that all the MEC clustering models outperform the non-clustering approach. In addition, the conditions in which specific clustering models yield the most optimal results are analyzed. Results aim to provide insights into cost-effective MEC deployment models.