This work investigates detectability and availability of effect-based tire-road friction information without costly fleet tests. The detection part focuses a recursive estimation which largely relies on the tires' self-aligning torque. As the tire-road friction depends on both vehicle and tire properties, a combined tire and front axle model was implemented. The approach shows promising results to differentiate between asphalt and snowy road segments in a traffic network. Detectability tables are the basis to investigate the availability of such information by using a traffic simulation. The results are visualized for selected road segments and can be used in automated driving functions.
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This work investigates detectability and availability of effect-based tire-road friction information without costly fleet tests. The detection part focuses a recursive estimation which largely relies on the tires' self-aligning torque. As the tire-road friction depends on both vehicle and tire properties, a combined tire and front axle model was implemented. The approach shows promising results to differentiate between asphalt and snowy road segments in a traffic network. Detectability tables ar...
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