For intelligent vehicles, a fast and accurate estimation of road slope is of great significance for many aspects, including the steering comfort, fuel economy, vehicle stability control, driving decision-making, etc. But the commonly used estimation methods nowadays usually demand additional sensors or complex dynamic models, causing increase in system complexity as well as decrease in accuracy. To solve these problems, this paper puts forward a real-time road slope estimation algorithm leveraging the relationship between pitch angle and road slope, which only requires low sensors cost and computational complexity. Firstly, a GNSS/INS fusion system is established to obtain the pitch angle with respect to the navigation frame, which couples the vehicle’s pitch angle in vehicle frame and road slope angle. Then, based on the different characteristics in frequency domain of the two components, frequency domain analysis is conducted and low-pass filter is used to separate out road slope signal. Besides, considering the slope change during driving, a parameter adaption strategy is designed in order to timely track changes of slope conditions. Experimental results show that the proposed method has a good real-time performance and the average error is below 0.3 deg even when the road slope changes rapidly.
