Urban road network signal control method and device based on vehicle path information

Abstract

The invention discloses an urban road network signal control method and device based on vehicle path information. The method specifically comprises the following steps: acquiring target path data, demand generation time data, speed data, road network geometric data and conflict phase data of all vehicles in a road network in a target time period; recording the number of iterations m = 1, and initializing the vehicle arrival time of each intersection; clustering arriving vehicles of the same lane into a motorcade, constructing and solving a single-point signal control model taking delay minimization as a target, and optimizing vehicle leaving time at intersections one by one; calculating the vehicle arrival time of each intersection in the (m + 1) th iteration, and if the vehicle arrival time is not converged and m =m + 1, continuously optimizing the vehicle departure time; and if convergence occurs, taking the vehicle arrival and departure time of the mth iteration as the final vehicle arrival and departure time, and obtaining an intersection signal control scheme. According to the iknvention, delay minimization is taken as a target, a signal control scheme of each intersection of the road network is optimized, and the service level of the road network is effectively improved.

Description

technical field [0001] The invention belongs to the field of traffic safety control, in particular to an urban road network signal control method and device based on vehicle route information. Background technique [0002] With the continuous development of intelligent networked transportation, the vehicle demand information in the urban road network can be obtained in advance, and the vehicle demand path and time information are applied to the signal optimization of the urban road network, which can effectively reduce delays and improve the service level of the road network . Therefore, the research on urban road network signal control scheme based on vehicle routing information is of great significance. [0003] Most of the existing urban network signal control studies focus on vehicle groups, using mesoscopic traffic simulation models such as the LTM (linktransmission model) model and the SF (store-and-forward model) model to describe the traffic state, and optimize Con...

AI Technical Summary

Problems solved by technology

These optimization strategies have certain practicability, but they are relatively rough and cannot reflect the specific driving and delay conditions of individual vehicles on the road network; most of the signal control variables are the green light duration under the fixed phase scheme, which is not flexible enough

Therefore, it can be considered that the adaptability of the existing technology to the signal control of the urban road network is insufficient

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