Fleet Mileage Calculation And Application Using Large-scale Real-time Positioning Data

The mileage of operating vehicles is an important basic data,which can be used as an important basic data for the work of estimating vehicle life,calculating energy subsidies,and estimating exhaust emissions.The traditional method of calculating driving distance based on on-board meters has the problems of large data collection workload,easy to falsify,and low accuracy.Therefore,in recent years,most management bodies of operating vehicles have begun to use on-board real-time positioning data(such as Beidou system,GPS,etc.)method.However,the civilian vehicle real-time positioning device usually has a low sampling frequency and a large positioning error,especially in the area where the signal is blocked in the city center.Therefore,in actual use,a processing algorithm needs to be used to convert the positioning data into an accurate mileage.Although there are currently some methods based on map matching,with the substantial increase in the loading of the positioning system,the scale of positioning data is very large.When processing large-scale positioning data,the matching efficiency of many algorithms is not ideal,giving practical applications Brought some trouble.In order to solve this problem,this paper proposes a distributed map matching algorithm based on large-scale real-time positioning data.The main research contents of this article are as follows:(1)At present,the algorithm based on map matching has the disadvantages of poor accuracy and low efficiency when facing complex roads in urban areas.This paper proposes a new type of map matching algorithm,which fully considers the information contained in the real-time positioning data,which can improve the calculation efficiency under the premise of ensuring accuracy.(2)In the face of large-scale real-time positioning data,the single-machine matching performance is poor and the time is long,which cannot meet the actual application needs.This paper proposes a distributed scheduling algorithm that can split,sort,and assign tasks,perform multi-node parallelized calculations,and greatly improve the calculation efficiency.(3)According to the algorithm proposed in this article,write examples of operating vehicle mileage and line network coverage,and show the advantages of the algorithm used in accuracy and efficiency.Compared with other map matching algorithms,the distributed map matching algorithm in this paper can improve the calculation accuracy of road dense areas in the city,and can efficiently process large-scale data,and greatly reduce the calculation time.