Design And Implementation Of The Analysic And Display System For Floating Cars' Trajectories

In the freeway traffic analysis and decision-making, analysts and decision-makers hope to find collections of vehicles in similar motion patterns during a specific period of time. Because the sets tend to reflect the vehicles in the comparison occurred during the aggregation phenomenon.On one hand, it has important significance to the traffic status prediction. because the sets contain information on the main roads of passing movement, indicating that congestion may appear in the same period of time ,but also reflect the way traffic between segments of AC quantities large, can predict the affected area when one certain road accidents happen. On the other hand,through further analysis of its main attributes, we can get more operational aspects of the regulation of the vehicle, which will provide more transportation decision-making support information.Currently, many of Guangdong Province passenger vehicles and freight vehicles are fitted with a GPS device, the Guangdong Province Traffic Data Center has collected a lot of GPS data returned by these floating cars in the province. However, because the original GPS data contains little semantics, it is difficult to extract the movement patterns of vehicles.To solve this problem, we use the classical map-matching algorithm of GPS data,make it from the original space matching latitude and longitude to the freeway space, and then according to the trajectory- divided principle and the linear reference technology to generate trajectories in close movement semantic.Then use density-based clustering method to obtain collections of vehicles in similar motion patterns. In this paper, on the basis of the above work, have designed and developed an analysis and display system for floating cars'trajectoryies. The system implements the analysis of floating car trajectories, and visually display the decision result combined with geographical information . It makes the results more intuitive, easier to understand and it will help a lot in traffic decision-making.