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This work proposes a two-stage estimation strategy to determine a heavy-duty vehicle's mass and road grade. The estimation strategy uses standard signals available through the vehicle control area network. The first stage of this approach utilizes an adaptive least-squares estimation strategy to determine the vehicle's mass and an estimate for a constant road grade. Due to the time-varying nature of the road grade, a nonlinear estimator that provides a more-accurate estimate of the road grade is then developed. Simulation and experimental results show, under a set of qualifying conditions, that both mass and road grade can be estimated with good accuracy.