Every U.S. vehicle recall from 2022 to mid-2026, checked against the signals a connected car already produces. The failure was often visible in that signal before the recall was issued.
When a car is recalled, every owner of that model year gets the same letter. Most of those cars were never going to fail. The defect lived in a slice of the production run, but the recall covers all of it, and it lands after the failures have already started.
Recalls work this way because a manufacturer can identify what it built, not what is actually breaking. So they are late, oversized, and physical. Since the start of 2022, 4,030 campaigns have put 147 million vehicles into recall action. We rebuilt the entire public NHTSA record and checked each recall against the signals a connected vehicle already produces. The failure was often there first.
A recall runs on the build sheet, not the failure.
A campaign pulls in the whole production run, then waits for the failures to show. Only a fraction of those cars ever fail, and a quarter of the recalled population is never brought in at all. The failure signature, meanwhile, often sat on the car's own bus for years. Run the recall on the signal instead: catch the signature early, call in the cars already showing it, confirm the remedy took, and close software campaigns over the air where the car allows it. This paper measures how far that reaches.
One thing to be clear about up front. These signals exist on the vehicle today, thrown off every time the car runs. But almost none are captured, transmitted, or analyzed: they are dumped at key-off, stranded inside a supplier's module, or never logged. When this paper calls a recall reachable today, it means a fleet could start collecting that signal with no new hardware, not that anyone collects it now. Today essentially none of it is used. Reading and processing it is the product.
| Manufacturer | Campaigns | Vehicles | L1 | L2 | L3 | L1+L2 reach |
|---|---|---|---|---|---|---|
| Ford | 376 | 43.6M | 70 | 70 | 236 | 20.0M |
| Stellantis | 182 | 15.6M | 37 | 38 | 107 | 7.6M |
| Honda | 77 | 14.1M | 7 | 13 | 57 | 3.8M |
| Toyota | 80 | 10.8M | 8 | 18 | 54 | 4.8M |
| Hyundai | 103 | 8.0M | 16 | 13 | 74 | 3.6M |
| VW Group | 164 | 4.6M | 12 | 54 | 98 | 2.8M |
| GM | 130 | 8.7M | 23 | 21 | 86 | 4.0M |
| Tesla | 63 | 12.5M | 31 | 1 | 31 | 12.3M |
We do not build the over-the-air pipe. From signals already on the bus, we catch the signature, flag the cars already showing it, and confirm the fix took. And we measure the dealer-path gap: where the remedy is code, but the car has no remote route to receive it. Tesla is the counter-proof. 30 software recalls, every one shipped over the air.
| Domain | Complaints | Crashes | Deaths |
|---|---|---|---|
| Powertrain / stall | 65,389 | 2,290 | 231 |
| ADAS (FCW/AEB/lane) | 30,403 | 2,806 | 151 |
| Braking / stability | 31,365 | 2,571 | 37 |
| Rear camera (backover) | 6,762 | 423 | 31 |
We classify every recall by where its failure signature lives as a signal, then read the worth in two layers and never blend them. The first is measured today: what the record proves is already being lost while the signal goes uncaptured, the dealer-path gap, the 2.89-year blind window, the repeat-remedy pool. The second is estimated recovery: what capturing and acting on the signal is worth, every assumption stated. The headline is always the measured layer; the estimates stack on top, in their own color, never hidden inside it.
Signals the car already produces but no one collects: powertrain, fuel, emissions, stability, ABS, and any fault it already flags. Two paths, no rewiring: read the OBD port, or emit signals the TCU already sees.
The ADAS, camera, airbag and BMS signals already exist inside Tier-1 modules; they are just not on a collectible bus. A standard API to emit them is a real integration, not full SDV architecture, and no new sensor or harness.
The mechanical and structural residual that carries no signal today. Full SDV architecture plus predictive models is where the system moves from remediation toward prevention. The long build, and the real technical ceiling.
| Access tier | Vehicles | Reach | Exposed burden |
|---|---|---|---|
| L1 today, no new hardware | 44.3M | 30% | $2.0 to 8.1B |
| L2 + standard Tier-1 API | 27.8M | +19% | $3.8 to 17.0B |
| L1 + L2 reachable | 72.0M | 49% | $5.8 to 25.1B |
| L3 full SDV, new sensing | 74.8M | 51% | $14.6 to 68.3B |
| All recalls | 146.8M | 100% | $20.5 to 93.4B |
Of 612 software recalls, about 329 were pure code that still forced a dealer trip, at roughly $40 to $120 a vehicle in reflash labor and logistics. Over-the-air would collapse most of that wherever the architecture allows a remote route.
Software sits a median 2.89 years in the field before its recall. Continuous signal compresses that window, and a smaller window means a smaller eventual recall.
26 software recalls (4.68M vehicles) cite a prior failed fix. Per-vehicle verification keeps the same owners from being called back twice.
Dealer-path software recalls carry roughly $0.7 to 2.2B in reflash-and-service cost (this paper's own cost band). The pure-code share could ship over the air, recovering much of it wherever the architecture allows a remote route.
A quarter of recalled vehicles never return, leaving the hazard on the road. Aiming outreach and service capacity at the cars that actually show the signature lifts completion: a 5-point gain on the 72M reachable vehicles is about 3.6M more cars fixed.
Software sits a median 2.89 years in the field before recall. Continuous signal compresses that window, so fewer vehicles are built with the defect before it is caught, and the eventual recall population shrinks.
This is a worked illustration, not a deployment. The recall is real: Ford fuel-injector fire, 694K vehicles, July 2025, and its public signal really did lead the recall by nearly two years. Here is how the loop would have run it:
Built from the full NHTSA ODI corpus compiled into a 977,000-row database, all vehicle recalls 2022-01 to 2026-06. Vehicle counts are campaign-exposure (potentially-affected units, overlap-inclusive), not unique VINs. Cost is an illustrative band from per-remedy assumptions, cross-checked against the AlixPartners ~$500 per vehicle industry blend (~$73B).
Access tiers are a keyword-and-component classification over NHTSA's own text, conservative by design, so L1+L2 at 49% of vehicles is a floor, not a ceiling. The complaint-based failure proxy and the targeting lever are directional, labeled modeled, never folded into the headline. A safety recall's legal population is the regulator's to set; available signal makes that population smaller when caught early, the remedy faster and verifiable, and for software remote. Each recall's tier follows from NHTSA's own published text, so every assignment is reproducible.