Real-time multimodal transport path planning based on a pulse neural network model

Abstract

A modified pulse-coupled neural network (MPCNN) model is designed for real-time collision-free path planning of multimodal transport choice in stationary or non-stationary environments. The proposed neural network is topologically organised with only local lateral connections among neurons. The optimisation networks model consists of transport distance, transport time, transit costs and transit time and other factors, and then all factors compose to weight of the networks to realise the transformation to solve the shortest path problem. The effectiveness and efficiency of the proposed approach is demonstrated through simulation and comparison studies.