Toll station vehicle emission prediction method based on vehicle specific power and model tree regression

A prediction method and specific power technology, which is applied in the field of transportation energy saving and emission reduction, can solve problems such as insufficient fuel combustion, vehicle queuing, and increased emission of pollutants, and achieve the effect of simple, feasible, intuitive, and easy-to-use methods

Pending Publication Date: 2020-05-08
SOUTHEAST UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Expressway toll stations are areas with a high incidence of intercity traffic congestion. The main reason is that the traffic capacity of the road section at the toll station is not only restricted by the inherent traffic capacity of the road itself, but also more likely to be restricted by the service capacity of the toll station.
Vehicles must slow down and enter the station to stop and wait for the toll payment, and then accelerate to leave the toll station, which often leads to continuous queuing of subsequent vehicles
More notably, the generation of such congested road conditions makes vehicles start and stop, and fuel combustion is insufficient, resulting in a sharp increase in the emission of hydrocarbons, carbon monoxide and nitrogen oxides
Due to the special dynamic characteristics of vehicles passing through toll stations, ordinary emission prediction models may be less applicable, and relevant research is urgently needed to fill this part of the gap

Method used

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  • Toll station vehicle emission prediction method based on vehicle specific power and model tree regression
  • Toll station vehicle emission prediction method based on vehicle specific power and model tree regression
  • Toll station vehicle emission prediction method based on vehicle specific power and model tree regression

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Embodiment

[0053] Taking the ETC lane and manual toll lane at the Xuejia toll station on the G42 National Highway as an example, the CO, HC, NOx and CO 2 Building a real-time mass emission rate model based on vehicle specific power and model tree regression. Firstly, the basic data of the toll station is obtained. The volume concentration of CO, HC, NOx and CO2 gas in the vehicle exhaust gas is collected in real time by the AUTOplus vehicle exhaust analyzer, and the GPS 16-HVS instrument is used to collect real-time data during emission measurement. To test the speed of the vehicle, the time of the two instruments should be adjusted to be consistent when collecting the two data; a total of 1352 experimental samples have been collected in the embodiment, of which 1092 samples are used as training data sets to build models, and 260 experimental samples are used as test data sets To evaluate and compare the pros and cons of the models.

[0054] The sample size collected in the embodiment o...

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Abstract

The invention discloses a toll station vehicle emission prediction method based on vehicle specific power and model tree regression. The method comprises the steps of basic data acquisition, basic data preprocessing, data modeling and application analysis. The basic data acquisition comprises acquisition of volume concentration, vehicle speed, acceleration and vehicle self-weight data of various gases in vehicle exhaust gas; wherein the basic data preprocessing comprises the steps of converting the mass emission rate of various pollution gases, calculating the specific power of the vehicle, and carrying out time synchronization on the mass emission rate and the specific power of the vehicle by using an interpolation method; wherein the data modeling is toll station vehicle emission model construction based on vehicle specific power and model tree regression on the processed data; the method is based on a model tree and a vehicle specific power (VSP) regression model, and can accuratelypredict the emission of gasoline vehicles and diesel vehicles at a toll station.

Description

technical field [0001] The invention relates to traffic energy saving and emission reduction technology, in particular to a method for predicting vehicle emission at toll stations based on vehicle specific power and model tree regression. Background technique [0002] In recent years, climate change and air quality issues have become a worldwide problem. Among them, traffic, especially the exhaust emissions from intercity traffic, is one of the important sources of air pollution. Exhaust gases such as particles, carbon monoxide, carbon dioxide, hydrocarbons, and nitrogen oxides emitted by vehicles during transportation will cause great harm to air quality and human health. Expressway toll stations are high-occurrence areas of intercity traffic congestion. The main reason is that the traffic capacity of the road section at the toll station is not only restricted by the inherent traffic capacity of the road itself, but also more easily restricted by the service capacity of th...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q50/26G06F30/20G06F17/18G01S19/52G01N33/00
CPCG06Q10/04G06Q50/26G06F17/18G01N33/0037G01N33/004G01N33/0047G01S19/52
Inventor 叶智锐孙卓群王超于泳波
Owner SOUTHEAST UNIV
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