Research On Path Planning Technology Based On Complex Network In Smart City

With the rapid development of economy,the process of urbanization is accelerating,and the scale of urban road network is increasing.At the same time,the economic develops accompanied with the increase of residents' vehicle ownership,which makes the problem of traffic congestion a huge challenge we face in today's society.Path planning technology is the main means to regulate the traffic condition in the traffic system.System science believes that structure determines function.Therefore,fully understanding the structural characteristics of road network has important theoretical and practical significance for implementing more scientific and effective path planning.In this thesis,the complex network theory is used to study the urban road network structure in many aspects.The main contents are as follows:This thesis uses the traditional dual modeling method to model the urban road network,and analyzes the statistical characteristics of complex network of urban roads.Then,the arc-arc dual modeling method,which has better guidance effect on path planning,is used to model the urban road network,and on this basis,three measurement indexes and five attack strategies are used to simulate the survivability of the road network.The simulation results show that roads with bigger degree and bigger betweenness centrality play a more important role in maintaining the structural integrity of road network and its ability to carry traffic flow.In this thesis,the road length,road congestion status,degree and betweenness are introduced into a gravitational field model.Aiming at the characteristic that the damage to both structure and function of road network will be more serious after damage to important roads,a heuristic path planning algorithm which can protect important roads is studied.By comprehensively measuring the four indexes,the algorithm finally realizes the effect of protecting important roads and improving the overall traffic capacity of the road network.This thesis uses Python to build a simulation scene based on Chengdu urban road network and DIDI vehicle trajectory data,and compares it with traditional path planning algorithms.The simulation results show that although the proposed algorithm increases the average path length by 8.8% compared with the traditional path planning algorithm,it can reduce 70.151% of the increase in estimated traffic time of the overall road network,of which 93% of the estimated travel time reduction is for important roads.