A Method for Estimating Traffic Demand at Signalized Intersections Influenced by Traffic Flow Composition

Abstract

The invention belongs to the technical field of intelligent transportation control, relates to a signalized intersection traffic demand estimation method affected by a traffic stream, and is applicable to trunk lines and regional road systems. Various vehicle types and platoon dispersing characteristics are considered, intersection entrance stop lines and an upstream section of an intersection entrance, a plurality of traffic stream data sets are acquired, and platoon dispersing coefficient calibration method is provided based on the data sets, so that a traffic demand estimation model is built. Besides, technical application processes of the model and the method are given and explained by a use case according to computer programming software MATLAB and traffic simulation software VISSIM.The results show that a new method can accurately estimate signalized intersection lane group traffic demands according to traffic streams formed by various vehicle types.

Description

technical field [0001] The invention belongs to the technical field of intelligent traffic control, and relates to a method for estimating traffic demand at signalized intersections influenced by traffic flow composition. Background technique [0002] With the rapid development of social economy, the increasing number of motor vehicles has caused the problem of urban traffic congestion to become increasingly serious. Signal timing optimization at intersections is an effective way to alleviate urban traffic congestion. As the basis of signal timing optimization, the accuracy of traffic demand data determines whether the signal timing scheme is reliable. [0003] In recent years, research results on traffic demand estimation at home and abroad can be summarized as follows: (1) From a macro perspective, estimate the annual traffic demand or daily traffic demand. The four-stage model requires a large-scale traffic survey to obtain the travel data of the origin and destination...

AI Technical Summary

Problems solved by technology

If the detection section is set at a position far upstream from the stop line, because the platoon dispersion phenomenon will occur when the fleet drives from the upstream to the downstream, the obtained change curve of the arriving traffic flow does not coincide with the change curve of the actual traffic demand; if the detection section is set at Near the stop line, the queue length of vehicles formed by signal control often exceeds the detection section, and the measured traffic flow at this time is essentially the flow of leaving traffic, so it cannot reflect the real traffic demand

When designing the signal timing scheme, in practice, the actual traffic flow at the entrance is often taken as its traffic demand, but this approach is not scientific

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