Tesla owners who alleged the company falsely advertised estimated driving ranges for its electric vehicles have been instructed to pursue their claims through individual arbitrations rather than as a class action, a federal judge ruled on Thursday.
U.S. District Judge Yvonne Gonzalez Rogers in Oakland, California, determined that the drivers had agreed to an arbitration provision for dispute resolution with the automaker when purchasing their vehicles.
See also:Ā Tesla Boosts End-of-Quarter Offer with 10,000 Free Supercharging Miles
The plaintiffs accused Tesla of fraudulently inducing consumers to purchase its cars by overstating the distance they could travel on a single charge. The lawsuits also alleged that Tesla, led by billionaire CEO Elon Musk, misrepresented the driving range displayed on vehicle dashboards. A Reuters special report in July revealed that Tesla had formed a secret team to suppress drivers’ complaints about driving range, a fact cited in both lawsuits.
Tesla and its legal representatives did not immediately respond to requests for comment. The company has previously described the claims in the lawsuits as “unmeritorious.” Attorneys for the plaintiffs either declined to comment or did not respond to requests for comment.
See also:Ā Teslaās Supercharger Network Opening to Non-Tesla EVs Could Become a Billion-Dollar Business
Judge Rogers’ ruling did not address the substance of the drivers’ claims. She did not dismiss the lawsuits and suggested she could issue an injunction against Tesla if the drivers successfully arbitrated their claims under California’s unfair competition law and other provisions.
The drivers’ attorneys had criticized Tesla’s push for individual arbitration as an attempt to evade responsibility for its alleged deceptive behavior.
See also:Ā 2024 Tesla Model 3 Highland: Is It Worth the Upgrade?
In January, Tesla adjusted its driving-range estimates for its EVs following the implementation of a new U.S. government vehicle-testing regulation aimed at ensuring automakers accurately reflect real-world performance.
