Road & Pavement Engineering Patents: Who Leads, Where the Gaps Are 2026
- Filing has cooled sharply. the tracked filing count fell 75% between 2021 and 2024, the last year the data can be treated as complete.
- Two IPC subclasses dominate the field. G01C (navigation/gyroscopes) and G05D (control of non-electric variables) each sit on 65.0% of the 20 records in scope, well ahead of every other class.
- The ranked leader holds 10 families. against a field of just four ranked assignees, so most of this space is still open to entrants who are not already on the list.
Filing growth compares 2021 (4 records) with 2024 (1) — a three-year span. 2024 is the most recent year we treat as complete: publication lags filing by roughly 18 months, so 2025 onwards are still filling in and any growth rate that ends there would understate the field.
What this landscape actually covers
This dataset tracks patent families filed against a search string combining civil infrastructure road terms with structural and monitoring concepts such as design load, ground deformation, structural response and infrastructure durability. In practice the returned records skew heavily toward autonomous-vehicle and telematics assignees whose filings touch road infrastructure incidentally — through positioning, route adjustment and vehicle-to-infrastructure sensing — rather than toward classical pavement-materials or structural-engineering applicants.
That composition matters for anyone using this page to scope a filing strategy: the record set is small, the receiving offices are concentrated in the United States, and the most-cited documents are autonomous-driving patents rather than pavement or structural patents. Read the technology composition and assignee sections with that lens before drawing conclusions about classical road engineering.
Filing trend and technology composition
20 published records sit in scope, filed mostly through the United States receiving office with a small share through the EPO. Publication lags filing by roughly 18 months, so the final one or two years in any chart will always look thinner than the underlying filing activity actually was.
A peak in 2017, then a steep pullback
Filings peaked at 4 in 2017. The most recent complete comparison point shows 2021 at 4 falling to 1 by 2024, a 75% drop over that three-year span. Because 2025 and 2026 are still filling in, that decline should be read as the last confirmed trend, not as evidence the field has ended.
Navigation and control classes dominate
G01C and G05D each appear on 65.0% of the 20 records, with B60W and G06Q each on 50.0%. G01S, B60L, G06F and G08G trail behind. Because records can carry multiple IPC classes, these shares add up to well over 100% of the record total — they describe overlap, not a partition of the field.
Shares are the percentage of the 20 records in scope. A patent can carry several IPC classes, so the shares add up to more than 100%.
Go deeper on Road & Pavement Engineering Patent Landscape with Eureka
This page is one run against one query. Ask Eureka your own question about road & pavement engineering patent landscape and every answer comes back with the patent numbers behind it.
Try EurekaA representative record from the corpus
Information processing device, information processing system, and information processing method
A configuration for notifying a driver of an allowable activity according to an automated driving level. The system acquires the automated driving level of a mobile device, retrieves an automated driving level-corresponding allowable activity list from an external server or storage unit, and notifies the driver of the activity permitted at that level.Abstract text condensed from the published filing; see the full record for complete claim language.
| # | Publication no. | Patent title | Citations |
|---|---|---|---|
| 1 | US10042359B1 | Autonomous vehicle refueling | 363 |
| 2 | US10324463B1 | Autonomous vehicle operation adjustment based upon route | 286 |
| 3 | US10395332B1 | Coordinated autonomous vehicle automatic area scanning | 215 |
| 4 | US10065517B1 | Autonomous electric vehicle charging | 190 |
| 5 | US20200317216A1 | Operator-specific configuration of autonomous vehicle operation | 108 |
| 6 | US20210039513A1 | Autonomous electric vehicle charging | 30 |
| 7 | US10828999B1 | Autonomous electric vehicle charging | 16 |
| 8 | US10691126B1 | Autonomous vehicle refueling | 13 |
| 9 | US20230025002A1 | Autonomous electric vehicle charging | 4 |
| 10 | US11920938B2 | Autonomous electric vehicle charging | 4 |
Citation counts reward older filings inside this corpus and should be read as a signal of influence within the dataset, not as a measure of current commercial importance.
Each row carries its publication number; clicking a row searches Eureka by that number.
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Three read-throughs on the data before drawing conclusions about where to file or watch.
The pullback is real but recent years are incomplete
The tracked filing count fell from 4 in 2021 to 1 in 2024 — the last year in the dataset that can be treated as complete given an 18-month publication lag. Years after 2024 will fill in further and should not yet be read as continued decline.
Navigation and control classes crowd out structural classes
G01C (distance/navigation/gyroscopes) and G05D (control of non-electric variables) each sit on 13 of the 20 records. Classical structural or materials IPC classes do not appear among the leading subclasses at all, which tells its own story about what this corpus actually contains.
A short ranked list with one clear leader
Only four assignees appear in the ranking this dataset returns, with the leading assignee holding 10 families. That leaves most of the technical space outside the hands of any single ranked filer, though the ranking itself is too short to support a concentration percentage.
Eureka can read the same corpus for gaps instead of for coverage: under-claimed branches adjacent to road & pavement engineering patent landscape, with the prior art for and against each one.
The assignee picture
The ranking returned for this search covers four assignees, led by one company at 10 families. That is a short list relative to the record total, and it is dominated by automotive and consumer-electronics filers rather than dedicated civil-infrastructure companies.
One assignee holds a clear lead
The top-ranked assignee in this dataset holds 10 of the tracked families, well ahead of the rest of the ranked field. That lead sits inside a road-adjacent autonomous-vehicle filing programme rather than a pavement-materials or structural-monitoring one.
Automotive OEMs file alongside insurers and electronics majors
Kia Corporation and Hyundai Motor sit in the same short ranked list as an insurance company and a consumer-electronics group, underlining that this corpus is really an autonomous-driving-and-infrastructure-sensing space rather than a classical road-engineering one.
Latest-year activity has gone quiet for tracked filers
Recent-year momentum data shows the insurance-company assignee and the electronics-group assignee both at 0 filings in the latest tracked year. Given the publication lag, that quiet reading should be treated as provisional rather than a confirmed stop in activity.
| Assignee | Recent year | YoY |
|---|---|---|
| State Farm Mutual Automobile Insurance Company | 0 | — |
| Sony Group Corporation | 0 | — |
What to do with this landscape
Three ways to take this analysis further, depending on whether the goal is freedom-to-operate, competitive tracking or claim drafting.
Check freedom-to-operate against the leading classes
Before drafting in G01C or G05D territory, run a focused clearance search against the 13 records each class holds — that overlap is dense enough to need individual claim review rather than a class-level read.
Explore Eureka for FTO screeningWatch the ranked leader's next filings
With one assignee holding 10 of 20 tracked families, a filing alert on that assignee is more informative than watching the field as a whole.
Set up assignee tracking in EurekaDraft into the under-claimed branches
Ground-deformation monitoring and pavement-embedded structural sensing do not appear in the leading IPC classes or the most-cited records — that gap is where a first claim has room to stand.
Map white space in EurekaCommon questions about this landscape
This dataset's ranking returns only four assignees, led by one company holding 10 of the 20 tracked families. The rest of the ranked list includes automotive OEMs Kia and Hyundai alongside an insurance company and a consumer-electronics group, which reflects how heavily this particular search skews toward autonomous-vehicle and infrastructure-sensing filings rather than classical pavement-materials patents. Because the ranking is short, it should not be read as a comprehensive map of every company active in road engineering broadly, only of the filers that matched this specific search string.
The confirmed trend shows a decline: filings fell from 4 in 2021 to 1 in 2024, a 75% drop over that three-year span, after peaking at 4 in 2017. However, because publication typically lags filing by around 18 months, the years immediately before the data cut-off are still filling in and should not be read as proof the field has stopped moving. Treat 2024 as the last year with a reasonably complete count, and revisit the trend once later years mature.
Navigation and control classes dominate: G01C (distance, navigation and gyroscopes) and G05D (control of non-electric variables) each appear on 65.0% of the 20 records in scope, with vehicle-control class B60W and business-data class G06Q each on 50.0%. Classical structural-engineering or pavement-materials IPC classes do not feature among the leading categories, which signals that this corpus is dominated by autonomous-vehicle and infrastructure-sensing applications rather than civil-structural ones. Anyone searching specifically for pavement-materials prior art should expect this dataset to under-represent that niche.
The search terms reference design load, ground deformation, durability assessment and monitoring sensors, but none of the leading IPC classes or most-cited records concentrate on those structural-monitoring concepts directly — they cluster instead around vehicle navigation and control. That gap suggests room for claims built around pavement-embedded structural sensing, ground-deformation monitoring networks, or durability-assessment data models that are not framed as vehicle-navigation inventions. A first claim in one of those branches would face less crowded prior art than a claim filed into G01C or G05D.
The most-cited records in this dataset are autonomous-vehicle patents such as filings on autonomous vehicle refueling and route adjustment, with citation counts in the hundreds. Citation counts inside any searched corpus tend to favour older records simply because they have had more time to accumulate citations, so a high count signals historical influence within this specific search rather than current commercial importance. Newer filings, including the 2023 representative record from Sony, will structurally show fewer citations regardless of their eventual significance.
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Disclaimer. This page is generated from Patsnap Eureka data drawn from a limited snapshot of global patent and scientific-literature records, and is provided for general information and reference only.
Patent data carries inherent limitations: recent filings (typically the most recent 18–24 months) are under-counted due to standard publication lag; counts may be reported at either a patent-family or a patent-record basis and are not always directly comparable; classification, applicant-name, and citation data may contain errors, duplicates, or omissions; and the underlying search query defines and constrains the scope shown. As a result, the analysis may be incomplete or inaccurate and may not reflect the full technology landscape.
Nothing on this page constitutes an exhaustive prior-art, novelty, freedom-to-operate, or validity search, nor does it constitute legal, financial, investment, or professional advice, and it should not be relied upon as such. Any patent, commercial, or strategic decision should be verified independently and reviewed with qualified patent, legal, and domain professionals. Patsnap makes no warranties, express or implied, as to the accuracy, completeness, or fitness for any particular purpose of the information presented.
Machine translation. Assignee and organisation names originally recorded in Chinese, Japanese or Korean have been rendered into English by an AI translation step so that the tables stay readable. These renderings are best-effort and may not match a company’s registered English name; the original name is what the underlying patent record carries, and it is what any Eureka query launched from this page uses.