The ranked assignee list in this dataset covers 100 companies counted by patent family, with one clear leader holding 89 records against a fifth-place count of 45 and a tenth-place count of 26. That gap between first and fifth place shows a genuine leader rather than a tight cluster, though the combined top 5 still account for only 12.6% of the 2,713 records in scope, meaning the great majority of activity sits in a long tail of smaller filers. Anyone assessing competitive position should look at both the leader's filing history and the breadth of that tail rather than assuming the field is a two- or three-way contest.

Filings peaked at 137 in 2020 and have declined from 131 in 2021 to 72 in 2024, a documented 45% drop over that three-year span. That is a real pullback through the last complete filing year, but 2025 and 2026 counts in any dataset like this are understated because publication typically lags filing by around 18 months, so the very newest years should not be read as proof of a continuing slide. A fair read is that the field cooled off its 2020 high, with the most recent trajectory still to be confirmed as later filings publish.

F16H, the gearing and transmissions subclass, appears on 22.2% of the 2,713 records in scope, making it by far the most heavily claimed area in this dataset. F16D, covering clutches and brakes, is a distant second at 7.1%, with vehicle control classes B60W and B60K each near 5%. Because a single record can carry multiple IPC codes, these shares add up to more than 100%, but the ranking itself is a reliable guide to where new claims are most likely to run into dense prior art.

US20220055623A1, filed by Hyundai Motor Company and published in February 2022, covers a specific method of estimating road-surface friction coefficient by deliberately inducing a wheel-speed difference through an added braking force on one axle while cancelling that braking effect with an added driving force on another axle. The claim is narrow to that dual-axle, force-cancelling estimation technique rather than to friction-coefficient estimation broadly, so it constrains designs that use this particular wheel-speed-difference method rather than blocking friction estimation generally. Teams working in this space should map their own sensing or estimation approach against the specific mechanism claimed before assuming broader exposure.

The dataset shows claim density concentrated in F16H gearing and F16D clutches and brakes, while adjacent areas such as vibration-mode sensing integrated into bearing assemblies, fatigue-crack detection in transmission housings, and wear-reduction coatings applied specifically to gear contact surfaces show up far less. These are not empty fields, but they carry a thinner claim record relative to the dense core, which makes them worth a targeted prior-art check before drafting. Non-automotive applications of friction-coefficient estimation are a similar pocket worth checking, since most of the estimation claims in scope are drafted around vehicle drivetrains specifically.