Whether more accurate traffic forecasts or higher uncertainty coverage improve route decisions remains unclear. This study adopts a frozen protocol that separates speed error, candidate‑path upper‑bound coverage, route selection, and realized loss. Using processed road‑speed data from Beijing and Chengdu, we build offline proxy tasks consisting of 150 origin‑destination pairs, three candidate paths per pair, and 14 test days per city. We compare raw 90th‑percentile path‑time bounds with jointly calibrated upper bounds under a minimum‑bound route‑choice rule. Joint coverage rises from 83.19% to 92.26% in Beijing M1, from 75.14% to 88.33% in Chengdu M1, and from 74.01% to 90.64% in Chengdu M2. However, the C2 metric increases lateness by 0.1633, 0.7848, and 0.9200 percentage points respectively, and mean travel time by 0.588, 3.082, and 4.418 seconds. In a separate Chengdu predictor comparison, a 14.91% reduction in speed mean absolute error accompanies a 1.4571‑percentage‑point reduction in lateness under C0. Thus, in these frozen tasks, joint coverage is not a surrogate for downstream route utility, and offline results do not establish online or causal benefits.
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