ROAD CURVATURE ESTIMATION SYSTEM

摘要

A processor (26) using a first Kalman filter (52, 52.1) estimates a host vehicle state from speed (U) and yaw rate, the latter of which may be from a yaw rate sensor (16) if speed (U) is greater than a threshold, and, if less, from a steer angle sensor and speed (U). Road curvature parameters (C0, C1) are estimated from a curve fit of a host vehicle trajectory or from a second Kalman filter (54, 54.1) for which a state variable may be responsive to a plurality of host state variables (72, 74). Kalman filters (52, 52.1, 54, 54.1) may incorporate adaptive sliding windows. Curvature of a most likely road type is estimated with an interacting multiple model (IMM) algorithm (2400) using models of different road types. A road curvature fusion subsystem (96) provides for fusing road curvature estimates from a plurality of curvature estimators (42.1, 42.2, 42.N) using either host vehicle state, a map database (88) responsive to vehicle location (86), or measurements of a target vehicle (36) with a radar system (14).