Read More: How Tesla’s Price Cuts Illustrate EV Ownership Cost Volatility for Fleets
Tesla Recalls 2.2M Vehicles for Incorrect Font Size on Warning Lights
The reason for the recall? An incorrect font size displayed on the instrument panel for the Brake, Park, and Antilock Brake System (ABS) warning lights.

The 2024 Tesla Cybertruck is one of the recalled vehicles due to incorrect font size on warning lights.
Photo: Tesla
Tesla, Inc. (Tesla) is recalling approximately 2,193,869 2012-2023 Model S, 2016-2024 Model X, 2017-2023 Model 3, 2019-2024 Model Y, and 2024 Cybertruck vehicles, according to the National Highway Traffic Safety Administration (NHTSA).
An incorrect font size is displayed on the instrument panel for the Brake, Park, and Antilock Brake System (ABS) warning lights.
As such, these vehicles fail to comply with the requirements of Federal Motor Vehicle Safety Standard No. 105, "Hydraulic and Electric Brake Systems" and 135, "Light Vehicle Brake Systems."
To address the issue, Tesla began releasing an over-the-air (OTA) software update.
Not Tesla's First Recall
In December, Tesla recalled approximately 2,031,220 vehicles due to Autosteer issues.
"In certain circumstances when Autosteer is engaged, the prominence and scope of the feature's controls may not be sufficient to prevent driver misuse of the SAE Level 2 advanced driver-assistance feature," the recall notice said.
In February 2023, the company recalled approximately 362,758 2016-2023 Model S, Model X, 2017-2023 Model 3, and 2020-2023 Model Y vehicles equipped with Full Self-Driving Beta (FSD Beta) software or pending installation.
More Safety

Managing Road Risk at Scale: Why Fleet Safety Needs a Data-Driven Framework
Insights from the FIA Road and Driver Safety Indexes reveal how to manage road risk on a larger scale.
Read More →
Stellantis Recalls 1.3 Million Jeep Vehicles Worldwide Over Fire Risk
Stellantis is recalling more than 1.3 million Jeep Wrangler and Gladiator models worldwide over a fire risk linked to power steering pump wiring.
Read More →
Coaching Is Not Training, Even When AI Is Doing It
AI-powered safety platforms can detect risky behaviors and deliver immediate feedback. But effective driver development still requires a foundation of training followed by coaching that reinforces those skills.
Read More →
How Emotions Behind the Wheel Can Affect Fleet Safety
During National Safety Month, fleets are encouraged to look beyond distracted driving and recognize how stress, fatigue, and emotional well-being influence driver performance and crash risk.
Read More →
Nominations Open for 2026 Fleet Safety Award
Nominations have officially opened for the 2026 Fleet Safety Award Winner.
Read More →
Turning Connected Vehicle Data Into Decisions That Matter
Fleet leaders have more data than ever, but turning that data into clear, actionable decisions remains a challenge. This white paper shows how leading organizations are using connected vehicle data to improve safety, reduce costs, and optimize fleet performance. Learn how to turn insight into action across your fleet.
Read More →
Cameras, Safety and Insurance: From Reactive Claims to Real-time Prevention
Commercial auto remains one of the most challenging and costly lines of coverage for fleet operators and insurers alike. Learn more about how to effectively address these issues from Onur Aksan, Enterprise Business Development Executive, Geotab.
Read More →
NAFA Fleet Safety Symposium to Collocate With 2026 Fleet Forward Conference
The daylong certificate program will precede the Fleet Forward Conference at the Gaylord National Harbor in Maryland.
Read More →
The Distractions You Can’t Turn Off: What Drivers Face Outside the Vehicle
Fleet drivers face constant visual, cognitive, and environmental interruptions the moment they hit the road. From roadside chaos to mental fatigue and digital overload, today’s biggest driving risks often come from outside the vehicle itself.
Read More →
FLASH Weather AI Launches First Deep-Learning Hail Prediction Model With High-Resolution Forecasting
FLASH Weather AI has launched a first-of-its-kind hail prediction model capable of forecasting hail size and arrival time at 1-kilometer resolution up to 55 minutes ahead, giving fleets and insurers critical time to prepare for severe storms.
Read More →
