Follower behavioural change based on natural patterns in traffic oscillation

Abstract

An understanding of the change in follower behaviour as a driver characteristic in traffic simulations is necessary because these behavioural changes are frequently observed in traffic oscillations. The change in follower behaviour due to traffic acceleration and deceleration waves can be classified according to different behavioural patterns resulting from different driver reactions. Combinations of existing behavioural patterns (under-reaction–timid, over-reaction–timid and constant over-reaction–timid patterns) were thus analysed. The method of analysis was based on an artificial neural network model at the microscopic level in order to simulate the extent to which follower behaviour deviates from Newell's car-following model. The most influential parameters of all the behavioural patterns were determined. Based on the under-reaction–timid pattern, decreasing the reaction speed resulted in a change in behaviour due to the development of safe spacing at the reaction point. In addition, follower spacing was the most influential in the over-reaction–timid pattern, resulting in increasing and then decreasing behavioural change. In the constant over-reaction–timid pattern, the follower's speed resulted in increasing and then decreasing the change in behaviour. The application of behavioural change to an intelligent transportation system would improve safety.