The aim of this work is to define and evaluate a “yaw rate error” (YRE) derived from naturalistic driving data to quantify driver steering performance during lane keeping. This measure of lane keeping performance is based on the predicted kinematic control error at any instance. Scope is limited to the demonstration that such a quantity exists, that can be computed from naturalistic driving data, and that it correlates with instantaneous control performance in real-world driving. The YRE is defined as a measure of conflict:​ the difference between current vehicle yaw rate and kinematic values required to be consistent with forward lane boundary crossing. A second, well-known measure is computed for comparison:​ the predicted time to lane crossing (TTLC). All data is obtained from naturalistic driving databases containing detailed information (over 200 signals at 10 Hz.) on driver input and vehicle response as well as aspects of the highway and traffic environment. As a continuously updated measure of the control correction required by an alert driver, it is expected that the YRE will be more informative of driving situations than the simpler kinematic measure TTLC. This latter measure is only loosely related to the closed loop control of vehicle motion. For example a very small TTLC can represent either a critical case where the vehicle is about to depart the lane and requires a large correction, or it could be a case where the vehicle is close to the lane boundary but with small lateral velocity requiring only a small correction. The YRE represents the severity of the possible lane departure in a natural way, accounting for current position, path direction, and path curvature. While no in-depth statistical analysis is conducted for YRE, it is proposed as a new tool for post-hoc analysis of driver steering performance during lane keeping.