01368023

Component

Traditionally, the amount of air pollutant emissions from motor vehicles—hydrocarbons, carbon monoxide, and oxides of nitrogen—is estimated from emission factors based on trip and vehicle miles traveled and aggregate measures of vehicle activity (e.g., average vehicle speed). This method is not reliable for urban networks, as it does not consider the effect of traffic signals and congestion. There is a need to predict vehicle activity by mode of operation, i.e., time spent in cruise, acceleration, deceleration, and idle to obtain improved emission estimates. An analytical model for estimating vehicle activity on signalized arterials with emphasis on oversaturated traffic conditions is proposed. The model depends only on system loop detector data on arterial links and signal settings as inputs and provides estimates of the distribution of time spent per driving mode, which consequently leads to more accurate vehicle emission estimates. The application of the proposed model on a real-world arterial shows that it accurately estimates the time spent and consequently the emissions per driving mode. The authors also show that smoothing arterial operations by optimizing the signal offsets significantly reduces the amount of emissions on the test arterial.

This paper was sponsored by TRB committee ADC20 Transportation and Air Quality

01362476

12-3899

English

16p

2012

Transportation Research Board 91st Annual Meeting

Digital/other

Figures; References; Tables

Arterial highways; Exhaust gases; Mathematical models; Mobile sources; Signalized intersections; Traffic congestion; Traffic oversaturation; Urban areas

Emissions models

Los Angeles (California); Santa Monica (California)

Environment; Highways; Operations and Traffic Management; I15: Environment

Transportation Research Board Annual Meeting 2012 Paper #12-3899

TRIS, TRB

Feb 8 2012 5:20PM