Uncertainty Analysis Of Emission Estimates At Link Level Based On Driving Trajectories

With the support of advanced information technology and big data,facing the construction demand of intelligent transportation and green city,the high-resolution and high-precision estimates of urban road traffic emissions is not only the basis for the launch and evaluation of energy conservation and emission reduction policies in various regions,but also a research hotspot in the field of transportation.At present,local emission estimate faces three challenges:the selection of emission model,the acquisition of local traffic/emission data and cost control.In terms of emission model,the emission model based on vehicle specific power?VSP?has become the mainstream due to its depiction of the field running state of vehicles and more direct parameter connection to emissions.In terms of traffic/emission data acquisition,satellite navigation,vehicle networking,video image acquisition,etc.all provide convenience for data acquisition.In terms of cost,due to the complexity of urban road transportation,vehicle trajectory data and emissions data acquisition needs a lot of time and economic cost,which has become an important shackle of urban emission estimates.Based on this background,this study aims at two important parameters in the emission model based on VSP?MOVES?-VSP distribution and emission rate,and carries out the quantitative relationship between the uncertainty of emission estimates and sample size.The main research contents are as follows:Uncertainty analysis of VSP distribution development.It is found that:the VSP distribution has certain uniformity,but its specificity cannot be ignored for emission estimates.The Root Mean Squared Error?RMSE?and overlap rate have consistency in uncertainty evaluation.For the development of VSP distribution,if the RMSE is less than 1%and the overlap rate is greater than 0.9,a specific speed bin of light-duty vehicles on restricted access and unrestricted access roads need 6900s and 10800s trajectory data respectively,and the buses need 3900s and 5760s respectively.If the RMSE is less than 0.5%and the overlap rate is greater than 0.95,the light-duty vehicles on restricted access and unrestricted access roads need 18540s and 36540s trajectory data respectively in a specific speed bin,and the buses need 13140s and 20880s respectively.Uncertainty analysis of emission rate calculation.It is found that:the two indexes of relative entropy and Euclidean distance are consistent in uncertainty evaluation.For light-duty vehicles,9600s emission data can meet the accurate calculation of CO₂,NOx,HC,CO emission rate,and 17000s for buses.Emission estimates.It is found that:If the calculation error of emission factors is less than 1%,light-duty vehicles need 12000s?restricted access roads?and 18000s?unrestricted access roads?trajectory data,and buses need 7500s?restricted access roads?and 5000s?unrestricted access roads?.When the emission data reaches 8000s and 20000s,light--duty vehicles and buses can carry out accurate?error is less than 1%?emission estimates.In the field road scene?From 8:00 to 20:00?,the error ranges of emission estimate of light-duty vehicles on restricted access roads and unrestricted access roads are[1.44%,13.43%]and[1.24%,6.05%]respectively.The emission calculation error decreases with the increase of traffic volume.The error ranges of emission estimate of buses on restricted access roads and unrestricted access roads are[5.88%,15.19%]and[4.58%,7.77%]respectively.The error is caused by the different operation modes of buses in different average speed bins.This paper studies the uncertainty of emission estimates from the two dimensions of VSP distributions and emission rates.The quantitative relationship between the uncertainty of emission estimates and the sample size of traffic/emission data can help reduce the cost of data collection for emission estimates and related research.In practical applications,the quantitative relationship between the uncertainty of emission estimates and the sample size of traffic/emission data has certain reference significance for cities or regions that lack traffic/emission data and have limited economic and time costs.