Software testing, a critical phase in the software development lifecycle, is often hindered by the time-intensive and costly manual creation of test cases. While automating test case generation could mitigate these challenges, its adoption in the industry has been limited due to difficulties in comprehending the generated test cases. To address this, our study presents an approach for clustering test cases and evaluates its impact on the comprehensibility of test suites through empirical research. Our approach clusters test cases based on their covered objectives, grouping together those with similar attributes to enhance developer understanding. The core of our empirical research evaluates developer agreement with our clustering method and contrasts the comprehensibility of clustered versus non-clustered test suites. Findings suggest a broad agreement among developers in favor of our clustering approach, with clustered test suites facilitating faster software maintenance tasks. Notably, the effectiveness of task completion remained comparable between both suite types. In summary, our research introduces and validates an innovative test case clustering strategy, striving to enhance the comprehensibility of automatically generated test suites.