Optimize Pollutant Emissions Through Adaptive Highway Management
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Optimize Pollutant Emissions Through Adaptive Highway Management

Filetype[PDF-566.29 KB]


  • English
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    Details:

    • Creators:
      Wang, Fei
    • Corporate Creators:
      California State University, Long Beach
    • Corporate Contributors:
      METRANS Transportation Center (Calif.)
    • Subject/TRT Terms:
    • Resource Type:
      Tech Report
    • Geographical Coverage:
    • Corporate Publisher:
      METRANS Transportation Center (Calif.)
    • Abstract:
      In this project, we investigated the possibility to reduce green house emission (mainly CO2) from urban highways by adaptive ramp meter control. QUADSTONE PARAMICS software was used to build a microscopic traffic model for a 4-lane highway section containing on/off ramps. A mathematical model of CO2 emission as a function of vehicle’s speed and acceleration was also developed. Total emission of simulated highway section was calculated under on a variety of ramp meter control scenarios and traffic densities. It has been found that the emission rate of greenhouse gases varies non-linearly with vehicle’s speed. While vehicles move at relatively high speed (i.e. greater than 50 mph), the emission rate increases monotonically with speed of vehicle. On the other hand, when vehicles move at extremely low speed (i.e. less than 20 mph), the emission rate is reversely proportional to vehicle’s speed. In addition, vehicle’s acceleration also plays an important role. This non-linear behavior of emission rate indicates the possibility to optimize greenhouse emission through smart speed and mobility control on urban corridors. A test model of a 1.5-mile 4-lane highway section with one on-ramp and one offramp was developed. A fixed time ramp meter is placed on the on-ramp and simulated the model at different scenarios by adjusting the red-time interval of the meter. It is observed that in light or moderate traffic senarios, the optimal red time interval increases with traffic density. However, when the traffic becomes very heavy or jammed, the optimal red time actually decreases. Our simulation also shows the overall emission decreases with highway speed limit. The fact that the red time interval needs to be reduced under heavy traffic in order to reduce CO2 emission indicates a trade-off between improving highway throughput and reducing CO2 emission. Optimization plans solely targeting for higher throughput not necessarily leads to lower emission, on the contrary, it may increase the emission in some cases. It is also observed that implementing ramp meter control works better for heavy traffic situations than light traffic ones; while speed limit control works better for light traffic situations.
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