Method for reconstructing running track for road vehicle based on multi-source data fusion

Abstract

The invention discloses a method for reconstructing a running track for a road vehicle based on multi-source data fusion. The method aims to comprehensively and accurately reproduce spatial and temporal distribution and an evolution principle of road traffic situation, thereby improving parameter estimation and prediction accuracy of the traffic situation and improving signal control efficiency. The method which is based on a variational theory of three-dimensional shock wave comprises the following steps of: firstly, estimating a slope of a forward-arc and a backward-arc by using fixed-pointdetector data to establish an initial road-space network diagram; secondly, estimating a curve of queueing propagation by combining floating vehicle data and signal timing data; finally, reconstructing a complete running track for the vehicles based on a shortest path algorithm under constraints of three dimensions including the floating vehicle track, a queueing boundary and the signal timing. According to the method for reconstructing the running track for the road vehicle based on multi-source data fusion, technical problems that the running track of the vehicle is difficult to accurately estimate under current congested situation, and higher permeability is required for current research based on sampling track data are solved.

Description

technical field [0001] The invention relates to the field of intelligent transportation, in particular to a method for reconstructing running tracks of arterial vehicles based on multi-source data fusion. Background technique [0002] Vehicle trajectories are the most comprehensive and complete expression of traffic flow operation status. They can not only reflect the vehicle's driving path on the road network, but also reflect the variation of vehicle speed with time and space, and contain very rich traffic flow information. With the development of new-generation information technology such as mobile Internet, the improvement of traffic informatization level has made the large-scale, continuous, automatic fixed-point and mobile detection data collection of urban road network a reality. Traditional fixed-point detection equipment (such as coils, video, geomagnetism, etc.) can directly obtain traffic characteristic parameters such as speed, flow, and occupancy at a certain ti...

AI Technical Summary

Problems solved by technology

[0005] Embodiments of the present invention provide a method for reconstructing vehicle trajectories on arterial roads based on multi-source data fusion, to at least solve the problem that it is difficult to accurately estimate vehicle trajectories in the current congestion state and the current research based on sampled trajectory data requires a higher penetration rate. technical problem

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