Analysis And Research Of The Highway Traffic Incident Detection Algorithm Based On PSO-SVM

In recent years, the state has vigorously the development of the transportation industry, the highway is very rapid developments in the field, by the end of2012, Chinese highway mileage has reached96,000kilometers, beyond the United States to become the world’s largest highway system. Highway development has brought many economic benefits for the community, but also because of highway traffic volume increases, traffic congestion, increased the chance of accidents, great highway capacity, reduce operating efficiency, or even cause casualties and property damage and other serious consequences. How to quickly and accurately detect the traffic incident as much as possible to improve highway capacity is the current issue of universal concern. Quality of highway traffic incident detection algorithm directly affect the efficiency of the traffic incident detection, and therefore of great significance to study the highway traffic incident detection algorithm.Highway traffic flow characteristics as well as the basic principles of the traffic incident detection analysis, by highway traffic incident detection in adaptive analysis applied to the support vector machine, to build a model based on SVM-AID, simulation experiment for SVM based on experience, the choice of the model parameters using PSO optimization algorithm and PSO algorithm has been improved by adjusting the inertia weight dynamically select the acceleration constant improvement strategies, and achieved good detection effect. Secondly, in this paper, in the fifth chapter chaotic combination with particle swarm optimization algorithm, using the chaos’s traversal property, randomness and other characteristics, and better able to escape from the local minimum, the globally optimal; build out based on CPSO-SVM model of freeway traffic incident detection, traffic incident detection using the model.The experimental data from1-880traffic flow database build a training data set and test data set of experimental data as a thesis. Simulation software uses MATLAB7.0. Learned through the analysis of the experimental results, the particle swarm optimization chaos optimization support vector machine algorithm has higher classification accuracy in detection rate and low false detection rate, good highway traffic incident detection results.