Online learning method for optimizing signalized intersection queuing length
A technology of queuing length and learning method, which is applied in the field of online learning to optimize queuing length at signalized intersections, can solve problems such as inability to accumulate experience and form management plans, achieve real-time performance and adaptability, and improve computing efficiency
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[0033] The technical solution of the present invention will be described in detail below in conjunction with specific examples of the accompanying drawings.
[0034]An online learning method for optimizing signal intersection queuing length, is characterized in that, comprises the following steps:
[0035] (1) Status, behavior, reward selection
[0036] 11) The vector composed of the queuing length of the key traffic flow in each phase is used as the state. In order to improve the calculation efficiency, the state space adopts a discrete form, and the discrete step length is an integer multiple of the average queuing length difference;
[0037] 12) The vector composed of the green light time of each phase is used as the behavior. For multi-phase intersections, the dimensionality disaster problem of behavior pairs will appear. The learning speed is the key to the practicality of online learning technology. In order to improve the learning speed, a dynamic behavior set is used. ...
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