Efficient multi-vehicle navigation based on trajectory vector features considering non-uniform destination distribution for emergency evacuation

Abstract

In recent years, large-scale events have been held frequently, and more and more people are participating in these activities. When encountering an emergency, it is necessary to quickly evacuate the participating people. A reasonable traffic evacuation plan is an important part of the efficient evacuation. However, the uneven geographical distribution of a large number of vehicles and participants poses a challenge for efficient evacuation planning. An efficient emergency evacuation plan needs to minimise evacuation time and traffic congestion. Reasonable route selection and traffic flow assessment are key to the evacuation plan. In this paper, we propose an efficient multi-vehicle navigation method based on trajectory vector features considering non-uniform destination distribution for emergency evacuation. First, we employ the CrossRank algorithm to extract the real-time state vector of roads and then navigate the vehicle based on these state vectors. In addition, spatial diversity theory is introduced into our model for the non-uniform distribution of multiple vehicle evacuation. We conduct a series of multi-vehicle navigation simulation experiment on a real taxi trajectory data set. The experimental results demonstrate that our approach is effective and efficient.