Analysis of Travelling Characteristics based on the Back Propagation Neural Network

The analysis of travelling characteristics is a crucial factor to smart city traffic management. It can help solve problems such as vehicle scheduling, resource allocation, etc. effectively. Traditional logistic regression analysis methods have low accuracy, cannot feedback optimization, so it's not practical. This paper proposes an analysis method of urban citizens' travel characteristics based on artificial neural network, theoretically proves the viability of neural network, and solves the problem of multi-parameter optimization of travel characteristics. The accuracy is high compared to the traditional logistic regression, and with more hidden layers added, the estimation accuracy will gradually increase, but the amount of calculation increases too.