Preprocessing apparatus for floating car data and method thereof

Abstract

The invention provides a preprocessing apparatus for floating car data and a method thereof, wherein the apparatus carries out a preprocessing treatment on the traffic data based on floating cars. The apparatus comprises the following components: an input unit used for inputting traffic data of a plurality of data points; a filtering unit used for filtering temporary parking data point from the input traffic data; and an output unit used for outputting the remaining data points as the traffic data after preprocessing after the filtration of temporary parking data points by the filtering unit. According to the invention, the temporary parking data can be removed to reduce the calculating intensity of subsequent calculation in road condition calculation based on floating cars and raise the calculation speed and accuracy.

Description

technical field [0001] The invention relates to the field of intelligent transportation, in particular to a data preprocessing device and method, which can preprocess traffic data based on floating cars and remove temporary parking data points therefrom. Background technique [0002] At present, floating car technology has been widely used in the field of intelligent road traffic, and traffic data based on floating cars can be used for road condition analysis, prediction, monitoring, etc. Before using the floating car data, it is usually necessary to preprocess the raw data to remove errors and useless data, and the remaining data are used for further subsequent processing. This preprocessing directly affects the calculation speed, strength and accuracy, so it is very important in the process of road condition calculation and analysis based on floating vehicles. Raw traffic data based on floating cars usually contains various types of data, such as normal driving data, temp...

AI Technical Summary

Problems solved by technology

[0003] Although the above method can remove errors and data beyond the area of ​​interest, it cannot remove other disturbing data, such as temporary parking data

In traffic data collection and road condition analysis based on floating cars, temporary parking data is an interference data that cannot be ignored, especially in urban environments with complex traffic conditions, where the number of vehicles is large and the traffic is not smooth, often due to vehicles in front, intersections, etc. and other factors, causing the vehicle to stop or drive very slowly

The floating car data collected in this case is abnormal data (referred to as temporary parking data in this paper), which will interfere with the correct calculation and analysis of road conditions

In addition, in the urban environment, the probability of such temporary parking data is relatively high, resulting in the collected floating car data containing more temporary parking data

This kind of data is easy to be regarded as normal data. If this kind of data is not filtered out from the floating car data before the road condition calculation and analysis, but directly used as normal data, it will lead to an increase in the calculation amount and a decrease in the calculation speed. slowdown and loss of computational precision

Images