The invention discloses a combined
estimation method for a
road junction dynamic steering proportion based on Bayes weighting. According to the method, three sub algorithms of an improved
Kalman filtering algorithm, an improved back-propagation neural network
algorithm and a
genetic algorithm are designed to solve the
road junction dynamic steering proportion by utilizing road segment traffic detected by all inlet roads and outlet roads of road junctions, historical data are combined based on the
road junction dynamic steering proportion, correction on historical and current
estimation deviation is considered comprehensively, calibration is carried out by utilizing a Bayes formula and weight is updated dynamically, and obtained results through the three sub algorithms are weighted to obtain the dynamic steering proportion estimated by the
combined method. Aiming at different
traffic flow situations, the dynamic steering proportions estimated by existing methods all have advantages and disadvantages in the aspects of precision and efficiency, the combined
estimation method can embody the advantages of all the methods on the whole, local oversize deviation is avoided, the combined estimation method has the advantages of being strong in adaptability, high in precision, good in stability and optimal in entirety, and can provide basic data supporting for
signal control and other real-time
traffic management and information service systems.