Autonomous Haulage Systems Patents: Who Leads, Where the Gaps Are 2026
- Thin, concentrated field. Only 11 published records and 12 ranked assignees, with a single leader holding 5 records against a fifth-place holder of 1.
- Fleet software outpaces on-truck autonomy. G07C and G08G each cover 45.5% of records, while control-layer classes like B60W and G05D each appear in just one record.
- Citation weight sits with one family. US11935416B1 and its continuation US20250131827A1 together carry the highest citation counts in the set, both on edge-computing fleet management.
What this landscape covers
This landscape tracks patent activity at the intersection of autonomous haulage and the operational problems that determine whether it works at a mine site: perception in dust, positioning accuracy, traffic interaction, remote supervision, obstacle detection and mixed fleet operation. The scope is deliberately narrow — 11 published records — because the search string combines autonomous-haulage terms with a specific set of operational failure modes rather than autonomy broadly.
Coverage runs from 2015-01-01 to the 2026-07-31 cut-off. Because publication typically lags filing by around 18 months, activity in the final year or two of any window is undercounted relative to what will eventually publish.
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Filing trends and technology composition
The dataset spans 2015 through the 2026-07-31 cut-off, with 11 published records in scope. Because publication lags filing by roughly 18 months, the most recent filing years are understated and should be read as a floor, not a ceiling.
A short, thin filing history with one clear peak
Filings sat at zero as recently as 2017 and built to a peak of 5 records in 2023, the high point of the entire window. With so few complete years once publication lag is stripped out, no growth rate can be stated reliably from this evidence.
Fleet tracking and traffic control lead; on-truck control is thin
G07C (time/attendance and checking devices) and G08G (traffic control systems) each cover 45.5% of the 11 records, with E01C (roads and pavements) and G01M (testing machine and structure balance) each at 36.4%. Because a single record can carry several IPC classes, these shares add up to more than 100% of the record total — that is expected and is the same denominator used in the chart.
Shares are the percentage of the 11 records in scope. A patent can carry several IPC classes, so the shares add up to more than 100%.
Go deeper on Autonomous Haulage Systems with Eureka
This page is one run against one query. Ask Eureka your own question about autonomous haulage systems and every answer comes back with the patent numbers behind it.
Try EurekaThe records shaping this field
Road quality monitoring — US20250162592A1
A road quality monitoring system is able to identify and display to end users, e.g. dispatchers and supervisors, road segments that are in need of repair. Each road segment may be given a road quality score based on suspension loading data, such as strut pressure data, from trucks traversing the road segment or by launch velocity data from trucks leaving a mine site, such as a shovel or a dumping zone.Filed by Teck Resources Limited, published 2025-05-22; shares a family lineage with the set's most-cited edge-computing fleet management filings.
| # | Publication no. | Patent title | Citations |
|---|---|---|---|
| 1 | US11935416B1 | Fleet and asset management and interfaces thereof associated with edge computing deployments | 12 |
| 2 | US20250131827A1 | Fleet and asset management and interfaces thereof associated with edge computing deployments | 3 |
| 3 | WO2023141727A1 | Road quality monitoring | 1 |
| 4 | US20250162592A1 | Road quality monitoring | 1 |
Ranked by citation count within the 11 records in scope; older records are structurally favoured by citation counting.
Publication numbers are shown where the record carries one (4 of 4 rows); clicking a row searches Eureka by that number.
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Browse MCP servers →What the filing pattern tells a decision-maker
With only 11 records in scope, this is a narrow evidence base — the patterns below are directional signals for where to look next, not a dense map of a saturated field.
A short history with one visible peak
Filings were at zero in 2017 and climbed to a peak of 5 records in 2023, the high point across the whole 2015-2026 window. The 2026 count is partial by definition since publication lags filing by roughly 18 months.
Fleet tracking and traffic control dominate
The two largest IPC clusters both sit at the fleet and dispatch layer rather than on the vehicle itself. Road condition and structural testing (E01C, G01M) each cover 36.4% of records, forming a secondary cluster.
One family carries most of the citation signal
US11935416B1 and its continuation US20250131827A1 (cited 3) both cover fleet and asset management tied to edge computing, well ahead of the two road-quality monitoring records at 1 citation each.
US leads, with Australia and India close behind
The United States receives 4 of the 11 records, Australia and India 2 each, and Canada, Peru and the WIPO PCT route 1 each — a spread consistent with mining-heavy jurisdictions.
Eureka can read the same corpus for gaps instead of for coverage: under-claimed branches adjacent to autonomous haulage systems, with the prior art for and against each one.
Who is filing, and how concentrated the field is
The ranking covers all 12 companies the data endpoint returns for this search — not a top-50 or top-100 cut. It is a short list, and the gap between the leader and the rest is the main structural signal here.
One company holds nearly half the leading filings
The top-ranked assignee holds 5 of the records tracked in this ranking, well ahead of the fifth-place holder's 1 record. Its lead family — the edge-computing fleet management filings — also carries the highest citation counts in the entire set.
A steep drop-off after the leader
From fifth place down through the rest of the 12-company ranking, holdings flatten out at 1 record each, including several individually named inventors and one engineering college. This is a field with one dominant player and a wide field of single-filing entrants.
Filing pairs cluster around academic and small-team entrants
The strongest co-assignee pairs in this dataset link individual named inventors and one engineering college, rather than joint filings between established commercial players. That suggests smaller, academically-linked filing teams working the space alongside the one large industrial leader.
| Assignee | Recent year | YoY |
|---|---|---|
| VIDHYA M P | 1 | — |
| SMITHA B | 1 | — |
| NAIR REKHA G | 1 | — |
| Teck Resources Limited | 0 | — |
| ARMADA SYST INC | 0 | — |
| SRI SAIRAM ENG COLLEGE | 0 | — |
| SHANMUGHA JEYASHREE B | 0 | — |
| SANDHIYA KARTHIGEYAN | 0 | — |
Where to take this analysis next
This landscape is a starting map, not a clearance opinion. The next steps depend on whether the goal is filing strategy, freedom-to-operate, or competitive tracking.
Run a claim-level design-around check
The two highest-citation records in this set — US11935416B1 and its continuation US20250131827A1 — sit on fleet and asset management tied to edge computing. Before building in that space, chart their independent claims against your own architecture.
Open the claim charts in EurekaTrack the under-claimed subclasses over time
Four IPC subclasses in this dataset carry only one record each. Set an alert on new filings in those areas to see whether the gap closes or stays open.
Set a monitoring alert in EurekaWatch the leader's continuation filings
The lead assignee has already filed one continuation on its core fleet management claim. Continuations often signal active claim-fence widening, so tracking future filings from the same family is worth the time.
Follow this family in EurekaFrequently asked questions
The assignee ranking in this dataset returns 12 companies, counted by patent family, and it is the complete ranking the data endpoint returns rather than a top-50 or top-100 cut. One company leads with 5 records, a fifth-place company holds 1, and a tenth-place company also holds 1, which points to a short, thin field rather than a crowded one. Readers should treat this as a snapshot of a niche, low-volume filing area rather than a mature, high-density one.
In this dataset the two largest clusters are fleet/asset tracking and checking systems (IPC G07C) and traffic control systems (G08G), each covering 45.5% of the 11 records in scope. Road quality and structural testing (E01C and G01M) each cover 36.4%. On-truck control elements such as hybrid vehicle control (B60W) and non-electric variable control (G05D) each appear in only one record, indicating the on-truck autonomy layer is thinly documented compared with fleet-level software.
The most-cited record in this set is US11935416B1, on fleet and asset management tied to edge computing deployments, cited 12 times, with its continuation US20250131827A1 cited 3 times. Two road quality monitoring filings, WO2023141727A1 and US20250162592A1, each carry 1 citation. Citation counts inside any searched corpus tend to favour older records, so treat these as a signal of influence rather than of what is currently most active.
Several IPC subclasses in this dataset carry only a single record each — B60W (hybrid/joint vehicle control), B64F (ground installations for aircraft), G01C (distance, navigation and gyroscopes) and G05D (non-electric variable control) — against the 45.5% coverage of the two leading clusters. That gap suggests positioning accuracy under dust interference and mixed-fleet control-loop claims are less occupied than fleet management or traffic control. A thin subclass is not proof of an open path on its own, but it is a reasonable starting point for a freedom-to-operate search.
US20250162592A1, assigned to Teck Resources Limited and filed 2025-05-22, claims a road quality monitoring system that scores road segments using suspension-loading data such as strut pressure, or launch-velocity data captured as trucks leave a shovel or dumping zone, and displays that score to dispatchers and supervisors. It does not claim road-quality monitoring in general; its scope is tied to those specific sensor inputs and the dispatcher-facing scoring pipeline. Anyone using a different sensing approach, such as vision-based surface inspection, would sit outside its specific claim language, though a design-around review of the full claim set is still advisable given its relationship to the applicant's higher-cited edge-computing fleet family.
In this dataset the United States receives the most filings with 4, followed by Australia and India with 2 each, and Canada, Peru and the WIPO PCT route with 1 each. That spread reflects mining-heavy jurisdictions alongside a PCT filing, consistent with a technology tied closely to mine-site operations in specific countries rather than a globally uniform filing pattern. The small overall count (11 records) means any single jurisdiction's share should be read cautiously.
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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.