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A Novel Road Grip Estimation Method Using a Vehicle as a Probe
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Winter weather road maintenance has been a topic of discussion among many state Departments of Transportation (DoT) within the US and numerous countries across the globe. Several research efforts have been conducted with the common goal of making this seasonal activity more efficient and/or cost-effective. Although promising results have come from these prior research efforts, road condition is still a missing piece of information essential for winter road maintenance decision making. Additionally, road condition can rapidly change during winter weather events, and any loss of traction can have catastrophic consequences. Hence the need for a system that is capable of not only determining the road condition, but also doing so before control of the vehicle is lost. This study introduces a new cost-effective method for measuring real-time road grip, which uses the driving vehicle itself as a probe (via onboard sensors). The relationship between wheel slip ratios and vehicle longitudinal acceleration, which is very similar to the relationship between wheel slip ratio and the tire longitudinal force, is used as the foundation of the estimation algorithm. Vehicle wheel speeds (used to calculate the slip ratio) were measured using Hall-effect sensors and an accelerometer attached to the vehicle chassis provided acceleration values. A new approach for processing the accelerometer output signal was developed in order to minimize the amount of noise present in the acceleration measurements. This approach consisted of isolating the two different longitudinal acceleration components found in the accelerometer signal by using the time derivative of wheel speed (kinematic acceleration). The filtered accelerometer and kinematic acceleration signals were then combined, yielding a better overall signal in comparison to the filtering results obtained when filtering the accelerometer raw output directly. A threshold curve used to identify road segments with potentially hazardous conditions was generated from the relationship between the wheel speed and the slip ratio and acceleration values were used to determine the road grip of these road segments. The results show that the presented estimation method can not only clearly distinguish between snow packed roads and dry roads, but can also determine different levels of road grip on snow/icy conditions. This information, if made readily available in real-time during winter weather events, would allow for better decision making and higher level of service, endorsing the use of the proposed system as a road grip estimation method.A secondary study consisted of using the component of the longitudinal accelerometer signal due to gravity to estimate road grade values. The main benefit being that this method can be used to estimate road grade in a moving vehicle (a challenge for simple accelerometers).Dynamic road grade measurements were compared with static measurements obtained using multiple accelerometers. These results showed good agreement, validating the new approach to estimating road grade in real-time.