Drifting in the Future: Stabilizing Path Following Drifting on High-Latency Vehicle Systems
Frederik Werner, Till Heintzenberg, Markus lienkamp, Johannes Betz
AI summary
Problem
Prior automated drifting research relied on research platforms with instantaneous torque and independent wheel actuation, leaving its applicability to production vehicles with significant powertrain delays and mechanically coupled axles uncertain.
Approach
The authors adapt a baseline drift controller by adding a state predictor to compensate for actuator latency, revising the control formulation for coupled axles, and integrating brake-based velocity stabilization to handle high-latency ICE powertrains.
Key results
- Designed a state predictor to compensate for ICE powertrain delays and align steering/torque dynamics.
- Developed a revised control formulation accommodating high actuation latencies and differential coupling.
- Integrated brake-based velocity stabilization to mitigate overshoots during drift transitions.
- Achieved robust circular and figure-eight drifting on a production sports car with lateral error ≤1.1 m and sideslip overshoot ≤0.06 rad despite >250 ms actuator delays.
Why it matters
Establishes that autonomous drifting can be reliably executed on production-ready vehicles, paving the way for advanced safety systems that stabilize cars beyond traditional control limits.
Abstract
Autonomously controlling and handling a vehi- cle at and beyond its stability limit is a mathematically and computationally demanding task. Prior demonstrations of automated drifting have been limited to research platforms with instantaneous torque delivery and independently actuated wheels, leaving their applicability to production vehicles with actuator latencies and mechanically coupled axles uncertain. To overcome these issues, we design a predictor to compensate for powertrain delays, develop a revised control formulation to accommodate higher actuation latencies as well as a differential coupling on the driven axle, and introduce brake-based velocity stabilization. This paper presents the controller framework, the model extensions, and real-world experimental results. We observe that our controller enables a production sports car with a combustion engine to robustly sustain circular and figure- eight drifts, limiting lateral error to 1.1 m and sideslip overshoot to 0.06 rad despite actuator delays exceeding 250 ms, while mitigating oscillations and maintaining stable path and sideslip tracking. In conclusion, our results establish that autonomous drifting is feasible on production-ready vehicles, opening path- ways to advanced safety systems capable of stabilizing cars in scenarios where traditional control fails.