01594568

Component

Due to industrial development and increasing number of vehicles, many countries are suffering from air pollution, especially smog. Estimating vehicle emissions can help provide valuable information to the public and authorities for better planning and decision making. High costs of directly measuring emissions have restricted government agencies from obtaining accurate and timely information. Therefore, estimating traffic emission based traffic demand and volume become necessary. Cellular activity data are cellphone communication records with cellular towers, generated during phone calls, texting, user data exchange activities, and all other cellular network system communication. This paper presents an innovative Hierarchical Clustering and Grid Mapping (H-G) approach for traffic and vehicle emission estimation using cellular activity data. This approach can reveal city-scale traffic dynamics and therefore estimate traffic emissions. Hierarchical clustering is proposed to compensate for the low location accuracy of cellphone activity data. Grid mapping utilizes cost matrix, which is calculated using a logit model from the road network, to project non-consecutive points to obtain the complete paths. The proposed method was tested using data from a midsize city in China. The results demonstrated the effectiveness and the rationality of the proposed model in traffic and emissions estimation. Different from traditional vehicle emission models which can only detect emissions in some fixed points, the proposed model can estimate traffic emissions in a citywide scale on the hour-by-hour basis.

This paper was sponsored by TRB committee ADC20 Standing Committee on Transportation and Air Quality. Alternate title: City-Wide Hourly Traffic Emission Estimation Using Cellular Activity Data.

01584066

16-5338

English

15p

2016

Transportation Research Board 95th Annual Meeting

Digital/other

Figures; References; Tables

Cellular telephones; Data collection; Estimating; Exhaust gases; Medium sized cities

Grid maps; Hierarchical clustering

China

Environment; Highways

Transportation Research Board Annual Meeting 2016 Paper #16-5338

TRIS, TRB, ATRI

Jan 12 2016 6:19PM