Machine-Learning based Transportation Network Sparsification for IoT Trucking Automation and Optimization

As the rapid manufacturing and industrial development, Internet of things (IoT) has become a key role in AI-smart transportation network especially for smart trucking automation and routing optimization. A maximum spanning k-tree algorithm is proposed to optimize the minimal loss of information from original network G to the spanning k-tree. The proposed network sparsification algorithm re-modelling IoT network in one of major U.S. trucking companies achieves great improvement of over performance. The novel Markov k-tree based network sparsification automates route generation, which practically results in increasing truck velocity, accelerating freight to recover service, creating a flexible inventory of loads-in-transit, re-balancing capacity and freight demand. In summary, it also gives a feasible approach to more practically and safely utilize auto-pilot truck based on a real-time sparsified IoT network.