Abstract: A recognition algorithm based on similarity data fusion was built with a multi-ultrasonic sensor
detection model to improve the recognition rate in artificial intelligent parallel vehicle parking system. Measured
data from multi-ultrasonic sensors were fused by using the method after threshold parameters of space edges
were determined. A multiple linear regression model was established to analyze the influence of vehicle speed
and transverse distance. A new method using data fusion with double sensors, a traditional method with single
sensor, and a mean value method with double sensors were compared to estimate recognition success rate.
The results show that the recognition rate with the new algorithm is 95.4% in simulated parking environment and
is 90% in actual environment, these rates are better than the rate by the two traditional methods.