Abstract
In this article, we use the neural network (NN) to study bicycle's conflict avoidance behaviors when crossing the un-signalized intersections under mixed traffic flow conditions. We introduce the basic concepts and learning rules of NNs, the structure and algorithm principle of back propagation (BP) NN, and modeling ideas and steps of applying NN to construct the bicycle conflict-avoidance (BCA) behavior model. We will then construct three types of BPNN-based BCA behavior models at un-signalized intersections. Finally we will verify the NN-based bicycle's conflict avoidance behavior model at un-signalized intersections by field data.
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