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

Authors: Tongjuan Zhao; Jiuhe Wang; Jianhua Zhang

Addresses: Yanshan University, Qinhuangdao, Hebei, 066004, China; Qinhuangdao Vocational and Technical College, Qinhuangdao, Hebei, 066100, China ' Yanshan University, Qinhuangdao, Hebei, 066004, China ' Hebei University of Science and Technology, Shijiazhuang, Hebei, 050018, China; Hebei Provincial Research Center for Technologies in Process Engineering Automation, Shijiazhuang, Hebei, 050018, China

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.

Keywords: neural networks; path planning; multimodal transport; wave propagation.

DOI: 10.1504/IJSPM.2017.085559

International Journal of Simulation and Process Modelling, 2017 Vol.12 No.3/4, pp.356 - 361

Received: 25 Jun 2016
Accepted: 13 Dec 2016
Published online: 30 Jul 2017 *

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