Yier Lin

Prof. Yier Lin


Research Focus & Metrics

Academic Career Length

1Year (2026-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

View All Publications
3 July 2026 in Applied Sciences
Verified
Journal Article
Open access
PDF file
JYJinzhe Yang
Jinzhe Yang
JLJianzheng Liu
Jianzheng Liu
YLYier Lin
Yier Lin
YHYang He
Yang He
ZZZhennan Zhou
Zhennan Zhou
This study presents a denominator-conditioned functional-coverage framework for rear-end automated emergency braking (AEB). The framework estimates what share of a declared modeled rear-end hazard denominator is controllable at a given intervention lead time. Ego–lead episodes come from NGSIM US-101 and I-80; the default D0 denominator is a modeled no-action counterfactual from episode-entry states, not a replay of observed future motion or a crash-rate estimator. A longitudinal brake-only replay model estimates policy-specific required lead times for transparent reference policies: a brake-only upper envelope, TTC-family references, a stopping-distance reference, and an RSS-style baseline. Under the default pipeline, the upper envelope saturates near 99%, the weak TTC anchor covers roughly half of the denominator, and stronger references reach about 95–96% frequency-weighted saturation. Duration filters change the saturation by at most 4.00 percentage points, and increasing physical-uncertainty realizations from R = 3 to R = 30 changes the saturation by at most 0.33 percentage points. An extended TTC-family audit shows that a coverage-only candidate reaches 99.00% saturation but 30.70% nuisance intervention, whereas a burden-constrained candidate reaches 97.88% saturation with 9.23% nuisance. The reported values are conditional controllability measures, not certification evidence or deployment-level crash-rate estimates.