Method and system for controlling traffic signal lamp in real time and intelligently

Abstract

A method for controlling a traffic signal lamp in real time and intelligently comprises the following steps: (a) setting a vehicle metering area; (b) setting two vehicle counting detection devices at the entrance and exit of the vehicle metering area respectively; (c) calculating the vehicle queue length in the vehicle metering area; (d) adjusting traffic signal lamp control parameters according to the vehicle queue length; and (e) setting a system resetting signal lamp at the entrance of the vehicle metering area to recount vehicles after the number of vehicles in the vehicle metering area is reset to zero. A system for controlling a traffic signal lamp in real time and intelligently comprises a set vehicle metering area, vehicle counting detection devices, a central processing unit and a signal lamp. The central processing unit calculates the vehicle queue length of each lane in real time by dividing the difference between the number of vehicles driving into the lane in the vehicle metering area and the number of vehicles driving out of the lane by a corresponding lane number, and then calculates the related parameters of the signal lamp based on the vehicle queue length and implements control. With the method and the system, traffic signal lamps can be managed in real time and intelligently, and the traffic efficiency is improved effectively.

Description

technical field [0001] The invention relates to the field of traffic management, in particular to the technology of intelligently controlling traffic lights. technical background [0002] With the progress of society, the contradiction between transportation resources and transportation demand has become increasingly prominent, especially in cities. In order to solve this contradiction, intelligent transportation systems (ITS) came into being, and they played an important role in continuously improving the utilization rate of transportation resources. However, as the starting point and end point of the intelligent transportation system (ITS), there is an obvious weakness in the current control of traffic lights, that is, the current intelligent transportation system (ITS) cannot obtain and apply information such as road vehicle queuing length, etc. Therefore, their adjustments to the phase, cycle length, and green signal ratio of traffic lights are based on historical data,...

AI Technical Summary

Problems solved by technology

However, as the starting point and end point of the intelligent transportation system (ITS), there is an obvious weakness in the current control of traffic lights, that is, the current intelligent transportation system (ITS) cannot obtain and apply information such as road vehicle queuing length, etc. Therefore, their adjustments to the phase, cycle length, and green signal ratio of traffic lights are based on historical data, that is, the data collected in advance can only be adjusted through modeling, and the data cannot be obtained in real time and applied synchronously. Some so-called traffic real-time measurement and control systems can only use the data collected in reality as the "rut of the vehicle ahead" to manage the "vehicle behind". The difference is that the data used has just happened, which seems to be more close to sync

It is not difficult to see from this that the current control of traffic lights is mostly based on previous data through modeling to manage the actual situation, rather than real-time adjustments based on the actual situation, so trying to use one or several modes to Inferring all traffic conditions, or using the data of the "car in front" to manage the "car behind", there will inevitably be distortion, especially because the modeling is staged and cannot be adjusted at any time, so sometimes the distortion will be very large Large, thus greatly reducing the accuracy and intelligence level of traffic lights control

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