Research on Path Selection Based on Moving Trajectory Big Data

In the era of big data, the rapid development of mobile internet technology and the popularization of mobile terminals have produced massive amounts of moving object trajectory data. These data contain rich temporal and spatial characteristic information, depict the behavior information of individuals and groups, and use relevant technologies to process trajectory data. Can dig out the behavioral characteristics of individuals and groups, which has important value for crowd evacuation, vehicle navigation, atmospheric environment changes, urban planning and other applications. Aiming at the current path dynamic planning problem, this paper builds a Spark distributed computing platform with improved ant colony algorithm to realize the efficient mining and in-depth analysis of moving trajectory big data; through the improved ant colony algorithm as the basis to analyze the path selection, and then for urban traffic management and Control provides theoretical basis and decision-making reference.