Research On Low Cost Monitoring Method For Key Parameters Of Expressway Cross Section Traffic Flow

A comprehensive grasp of the real-time traffic status of a wide range of expressways will help the traffic management department to quickly respond to emergencies and traffic jams.Therefore,it is necessary to apply traffic information detection technology to monitor the entire highway.However,the cost of existing traffic information detection technology is relatively high,and it does not have the conditions for high-density deployment and large-scale promotion.Therefore,on the basis of the existing research results,the paper has carried out research on low-cost monitoring methods of key traffic flow parameters in view of the high cost of existing detection technology.Based on the extensive analysis of the current research status at home and abroad,the following research is carried out around the key parameter monitoring methods of traffic flow.First,analyze the definition and correlation of traffic flow state parameters,use traffic volume,speed,and density as the key parameters to describe the macro traffic flow state,and clarify the redundancy of the rest of the traffic flow state parameters.Based on literature and market research,analyze the advantages and disadvantages of the existing traffic information detection technology,and determine the infrared detector as the prototype sensing device.Analyze the correlation between the infrared detector observation parameters and the traffic flow state parameters,take a single traffic flow parameter to estimate multiple traffic flow parameters as the goal,and clarify the necessity of establishing a speed-density model and a flow-density model.Secondly,based on the generalized Logistic curve,the speed-density model and the flow-density model are established;the basic section of Chongqing G50Shanghai-Chongqing Expressway is selected as the test section to collect traffic flow sample data;based on the measured data,the model parameters are calibrated.Third,the prototype architecture is designed with six modules: information collection,information processing,data transmission,data terminal,warning and guidance,and power supply device.Through the comparison and selection of key equipment,TXF-125 E as the prototype infrared detector,STM32F105RCT6 chip as the prototype’s main controller,SJDCB as the solar charging management device,S473 as the prototype wireless data terminal,and HD-150 as the prototype ’ s guide light.The prototype uses the main controller as the core,equipped with analog-digital converters,wireless transmission devices and other modules to design prototype hardware.The prototype adopts Vue2.x,Ant Design Vue framework,and the software functions of the prototype are designed based on C#,JS,and Html language.And build the software platform with the visual operation interface of the Web browser and the SQL Server database.The prototype was designed and produced and tested,and it was found that the prototype was running stably and met the design requirements.Finally,the basic section of Chongqing G75 Lanhai Expressway,the basic section of G5001 Ring Expressway,and the basic section of G5013 Yurong Expressway were selected as test sections to collect traffic flow data.Analyze the difference between the measured data of the prototype and the measured data of the microwave detector under different road sections and different lane conditions,calculate the absolute error of the traffic flow data,and clarify the effective range and failure range of the prototype under different road sections and different lane conditions.According to the absolute error analysis result,the cause of the error was identified,the invalid traffic flow data was corrected,and the accuracy of the prototype was verified.The research results show that the difference between the free flow data collected by the prototype under different road sections and different lane conditions and the free flow data collected by the microwave detector is small;the non-free flow data collected by the prototype under different road sections and different lane conditions and the microwave The difference between the non-free flow data collected by the detector is large and needs to be corrected.After calibration,the relative error of the non-free flow data collected by most prototypes is less than 15%,which is verified to basically meet the accuracy requirements.Therefore,the use of a detection prototype embedded based on the generalized Logistic curve speed-density model is helpful to solve the problem of high-density deployment and use of highway traffic flow detection equipment.