Research On Highway Map-matching Algorithm Based On Floating Car Technology

In recent years, as a sign of the economic and social prosperity, the vehicle populationhas shown a trend of rapid growth with the rapid pace of economic development in China.Therefore the traffic congestion is also on the rise, becoming the most important issue to besolved in metropolis and medium-sized cities. How to reflect the traffic conditions on theroad in time, to provide accurate guidance information for travelers and to avoid traffic jamseffectively is an important part of the field of intelligent transportation that has been focusedon. As an indispensable technology in the traffic information service system, GPS floatingcar technology has become a key to solve urban traffic problems nowadays. Map-matchingtechnology is the core technology in the field of vehicle navigation of the new generation ofintelligent transportation system, and that improve the match efficiency of it is an importantmeans to induce vehicle effectively, to optimize public transportation, to accurate trafficinformation. Highway, as an important part of our transportation system, is of the very rapiddevelopment momentum in recent years. Regarding to the GPS information for keyoperating vehicles on the highway, this paper presents a highway map-matching methodwhich is based on floating technology.Relying on the subject of the National High Technology Research and Development(863Program)“the multi-source and multi-dimension urban traffic state perception andinteraction processing”, according to problems in the GPS data pre-processing andmap-matching method of floating car map-matching technology molded domestic andabroad at this stage, and combined with characteristics of vehicles and network of thehighway in China, this paper adopts mathematical statistics, artificial intelligence, GIS andother advanced technical methods to focus on the highway map-matching algorithm which isbased on the floating car technology. Specific research contents are as follows:(1) Introduction. According to summarizing the current status quo of map-matchingalgorithms based on the floating car technology domestic and abroad, analyzingshortcomings of related technologies at this stage domestic and abroad, discussing thepurpose and significance of the study of the paper, and combined with characteristics of the highway in China, the idea of research and arrangement of chapters of the paper aredetermined.(2) Data processing and analysis of floating car GPS. By means of brief introduction ofthe information collection system of floating car, the mechanism and process of GPS floatingcar data, a pre-processing method which is suitable for the highway floating car GPS data isproposed. To evaluate in line with the evaluation methods and related indicators of dataquality, to ensure the source of floating car GPS data is true and reliable, accurate andeffective, so as to provide a highly reliable protection of data basis for the nextmap-matching algorithm.(3) Highway map-matching algorithm based on floating car technology. Descriptcommon map-matching methods briefly, introduce basic principles and contents of commonmap-matching methods and analyze comparatively of them, select the point-linemap-matching method as basic research direction by characteristics of highway network andthe traffic flow by introducing distance criterion, the direction angle criterion andconnectivity criterion.(4) Validation and improvement of the algorithm. Verify the effectiveness through theactual highway data. And to improve the algorithm in accordance with the matchingcondition of highway network of example validation, so as to construct an algorithm modelwhich is more efficient, more accurate, more suitable for highway and based on floating carmap-matching, making the matching algorithm of stronger adaptability and highereffectiveness.(5) Summary and prospect. Summarize the research contents and results achieved in thepaper comprehensively, point out the shortage of the paper, and look into the future forfurther research work.