The cubic polynomial clothoidal approximation is widely used for road lane modeling in vehicle applications such as adaptive cruise control, collision warning, lane departure warning, autonomous steering etc. For applications that apply multi-sensor data fusion to form the estimate of the road lane model, we demonstrate that the cubic polynomial clothoidal approximation is a poor parameter space due to large sensitivity to coefficient errors. Small systematic or random errors (wise) lead to substantially similar lane geometries, but significantly different clothoid parameters.
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