TBNAI
Joint upper-bound coverage and route-choice utility: an empirical evaluation on two urban proxy tasks
Publication: cs.AI updates on arXiv.org
Author: Jianing Long, Xiaobin Li, Wuming Lei, Weiguang Wang
Source published: 07/10/2026, 04:00:00 UTC
Briefing created: 04/11/2026, 02:40:26 UTC
Based on a feed excerpt; full article content has not been acquired. Source evidence retrieved 08/10/2026, 02:18:24 UTC.
Briefings
This study evaluates whether improved traffic forecast uncertainty coverage enhances route decision quality using offline proxy tasks in Beijing and Chengdu. Results show that while joint upper-bound coverage increased from 83.19% to 92.26% in Beijing M1, it increased lateness by 0.1633 percentage points and travel time by 0.588 seconds. In Chengdu M1, coverage rose from 75.14% to 88.33%, but lateness increased by 0.7848 percentage points and travel time by 3.082 seconds. A separate Chengdu predictor analysis found that reducing speed MAE by 14.91% reduced lateness by 1.4571 percentage points, suggesting coverage alone does not guarantee better outcomes.
Key points
- Joint upper-bound coverage increased from 83.19% to 92.26% in Beijing M1, yet increased lateness by 0.1633 percentage points and travel time by 0.588 seconds.
- Joint upper-bound coverage increased from 75.14% to 88.33% in Chengdu M1, yet increased lateness by 0.7848 percentage points and travel time by 3.082 seconds.
Context
Researchers tested if higher uncertainty coverage improves route decisions using offline proxy tasks with frozen protocols. They used processed road speed data from Beijing and Chengdu to construct tasks with 150 origin-destination pairs, three candidate paths, and 14 test days per city.
Limitations
Results are limited to offline proxy tasks and do not establish online or causal benefits. The study does not account for real-time traffic dynamics or dynamic route adaptation.
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