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Incremental multistep Q learning (Q( lambda )) combines Q learning and TD(lambda ). Theoretically, Q(lambda ) has better performance than Q learning. The goal of the paper is to test the performance of Q(lambda ) for adaptive traffic signal control. For Q(lambda ), the state is total delay of the intersection, and the action is phase green time change. The(More)
Adaptive and coordinated signal setting has been research emphasis. Cycle, split, and offset are three important parameters. Lessons and experiments about adaptive signal control have shown that cycle and phase sequence renewal interval should be less than 20 minutes. So frequently optimized parameters are split and offset. For Webster signal setting(More)
Multiband model of bandwidth optimization assumes that all the vehicles have the same speed. But there is traffic flow dispersion because of different vehicle performance. Traffic flow dispersion has been described by normal distribution and geometric distribution. The paper integrates traffic flow dispersion model into multiband model to optimize bandwidth(More)
With the consideration of the effect of non-motor vehicles on other lane without isolation belts, a modified coupled map car-following model is put forward. According to the feedback control theory, the stability conditions of the current vehicle influenced by non-motor vehicle on other lane are gained. The corresponding numerical simulations confirm the(More)
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