Do these 3 things before closing this tab:
1Repair Windows errors before they cause bigger problems2Fix the driver behind crashes, sound loss and screen glitches3Clear out junk files and repair common Windows errorsToyota Research Institute and Stanford Engineering demonstrated two full-size Toyota GR Supras drifting in tandem, with the chase car adapting to follow the lead car without colliding. Stanford reported that they came within 10 inches of each other at times and reached speeds of up to 35 mph. Those were conditions reported for a controlled research demonstration—not a feature or safety capability established for consumer cars.
What the self-driving cars did
Announced on July 23, 2024, after nearly seven years of collaboration, the project paired a lead GR Supra with a chase GR Supra. The lead car followed a planned drifting path. The chase car adjusted its trajectory in response, aiming to stay close while avoiding contact. Toyota and Stanford described both cars operating near the limits of control.
Drifting is a controlled maneuver in which a vehicle continues along a chosen direction after its tires exceed normal traction. In tandem drifting, the second vehicle has an added challenge: it must respond to the lead car’s movement while preserving a safe gap. Stanford reported speeds up to 35 mph and separation of less than 10 inches at times; neither figure means the cars maintained that exact distance throughout the run. Stanford Engineering’s account describes the demonstration.
How the control system worked
Repeated planning with nonlinear model predictive control
The teams used nonlinear model predictive control (NMPC), which repeatedly calculates a vehicle’s planned trajectory and control inputs while accounting for objectives and physical or hardware constraints. The lead car’s objective was to sustain its planned drift. The chase car also had to follow the lead and avoid a collision. Toyota said the optimization was solved and re-solved up to 50 times per second. That is the reported update rate for this project, not a general specification for self-driving cars. Toyota Research Institute’s announcement explains the approach.
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Learning about tire behavior and sharing information
Toyota’s description includes a neural-network tire model that learns from driving experience. The cars exchanged information over a dedicated Wi-Fi network, including their relative positions and intended trajectories. Stanford says GPS guided the vehicles. Because track conditions can change over short periods, the teams also described learning from successive trips to the track.
Why researchers study driving beyond normal grip
When tires are sliding, a vehicle can be difficult to control using methods designed for ordinary grip conditions. Drifting gives researchers a way to investigate vehicle behavior near or beyond those limits. Toyota and Stanford say some of the physics resemble what a car can experience on snow or ice, where a driver or automated system may need to manage a slide.
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Stanford professor Chris Gerdes, co-director of the university’s Center for Automotive Research, said the project had already led to “new techniques for controlling automated vehicles safely on ice.” That describes a potential research application, not proof that the tandem-drift system itself has been deployed in cars or validated on public roads. Toyota’s announcement quotes Gerdes on the connection between drifting and low-traction conditions.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What the demonstration does—and does not—show
The tandem drift is evidence that two full-size vehicles could coordinate a demanding, close-proximity maneuver in a controlled track setting. It is not evidence that consumer vehicles can safely perform the same maneuver, that the system prevents crashes, or that its performance has been established in public-road conditions. The organizations presented the work as research into vehicle control and safety, not as a production feature.
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A 2024 peer-reviewed paper offers related technical context: it describes NMPC for controlling a vehicle in the unstable sliding-tire regime and racetrack experiments with a modified GR Supra, including transitions between drifting and grip driving. It is related autonomous-drifting research, not confirmation that every technique in the paper was used in the tandem demonstration. The paper is available through Science Robotics.
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