Modelling And Experimental Verificating Of Traffic Information Active Push Based On LBS

As the vehicle amount increases continuously,the contradiction between supply and demand of urban transport is becoming increasingly acute.Traffic information service is an effective measure to adjust the time and space distribution of traffic flow and improve the capacity of road network,and it is widely used in urban traffic management.Research shows that about 80%of the information is closely related to the position in real life.Therefore,the combination of location service and traffic information service has become the development trend of traffic information service.The model of traffic information active push based on LBS can effectively solve the driving environment problems such as information overload and information competition,reduce the waste of time and resources,and ease the contradiction between supply and demand of traffic.This study aims to provide an effective solution for traffic information active push,provide the support for promoting intelligent and humanization of traffic information service system.With the location information provided by the fusion positioning algorithm,this paper puts forward a model of traffic information active push based on LBS,has completed the overall design of the active push system,the hardware and software design,and verified the effectiveness of the active push model.Firstly,this paper summarizes the present situation of domestic and foreign research from the aspects of active push and location acquisition,and puts forward the research content and technical route.Secondly,on the basis of introducing the system structure and key technology of the location service system,summarize the present situation and problems of traffic information service system.Then,the fusion location algorithm of GPS,DR and WIFI based on BP neural network was designed for the research object in this paper.With the help of kalman filtering and quantum particle swarm to fuse these three position technologies,this algorithm can achieve high precision positioning.With the location information provided by the fusion positioning algorithm,this paper puts forward a model of traffic information active push based on LBS from the perspective of location service,it includes model features,push content,push mechanisms,and push algorithms.In order to validate the push model,the overall design of the active push system is proposed,and hardware,software,database are designed in detail.Finally,the proposed fusion positioning algorithm and the active push model are verified by real vehicle test based on the active push system.The effectiveness of the fusion positioning algorithm is verified by using the data of outfield vehicle test.This paper considered two scenarios of accident early warning and road conditions prompt,and verify the effectiveness of active push model by analyzing the feature parameters.This paper does some distributed feature analysis of active push response time,and at the same time,the sensitivity analysis of the response time was carried in push distance and speed.Outfield test results show that the fusion positioning algorithm improves the positioning accuracy.The positioning accuracy has increased by 87.06%and 68.71%,compared with positioning algorithm based on kalman and positioning algorithm based on quantum particle swarm.Using the design system to analyze the active push model,the test of traffic information active push shows the system can provide real-time location service for vehicle mobile terminal in within one to three seconds,such as accident early warning and road conditions prompt.Also the system can adjust the active information service strategy in real time with respect to the position of vehicle,the road network familiarity and the vehicle speed.In addition,the sensitivity analysis shows that with the increase of push distance or speed,the response time grows slowly at first,then logarithmic growth and steady growth at last.With the speed and the relative distance gradual increasing,response time of the system increases gradually and very close to three seconds.