Abstract: The vessel traffic flow is the foundation of decision makings related to the design ,planning and manage‐ment of channels .This paper investigates the traditional vessel traffic flow forecast model of single cross section in water‐way ,and studies continuous cross section model based upon state space and Kalman filtering .The space state model is de‐veloped based on a multi‐dimensional linear regression analysis of the time series formed from the traffic flow at the multi‐ple cross sections .Kalman filtering is used to recursively forecast the vessel traffic flow at the multi cross sections .In the study ,the vessel traffic flows at the Wuhan Yangtze Bridge and Wuhan Yangtze No .2 Bridge in the City of Wuhan ,Chi‐na were analyzed to test the proposed model .The result shows the error decreases 4 .59% and 0 .97% respectively ,com‐paring to the results from the traditional forecast model using single cross section .In addition ,the real vessel traffic flow collected at Chaotianmen ,Wanzhou and Wushan in Chongqing ,China were also used to compare the proposed model with the single cross section model ,which results a 1 .08% ,4 .28% ,and 3 .54% decreases respectively .The test results indi‐cate that the proposed model can provide more accurate vessel traffic forecast .