This research intends to develop a microscopic framework to model the airport related traffic and emission implications. An approach to calibrate the driving behavior parameters of the traffic simulation model in the framework is proposed. A case study for Intercontinental Airport of Houston (IAH) is presented. The microscopic framework integrates a microscopic traffic simulation model and a modal emission model. A GA-based calibration approach defines the index of simulation accuracy as the Sum of Squared Errors (SSE) between the collected speeds and the simulated speeds at the pre-defined cross-sections along the road. The computer program implementing the GA-based approach is developed to search for the optimal parameters values. The field speed data are collected using the GPS system. It is found that the calibrated optimal values of the VISSIM driving behavior parameters result in a 50% decrease of the SSE value. The produced emissions of each vehicle show that the emission profiles reflect well the trends of the acceleration/deceleration. The emission results show that in the year 2002, the vehicles going in and out of IAH terminal area generate 2948 tons of CO2, 1.3 tons of HC, 13 tons of CO and 3.0 tons of NOx. These results can be referred by urban transportation planners when they conduct the airport-involved travel demand forecasting. The microscopic framework can not only assist in the operational-level analysis of the mobile source emission implications around the airport, but also provide a powerful tool to assist in the overall airport design and planning. The GA-based calibration approach can be used not only for airport roads, but also for other road networks.
Airport Related Traffic and Mobile Emission Implications
2003
138 pages
Report
Keine Angabe
Englisch
Air Pollution & Control , Air Transportation , Transportation & Traffic Planning , Transportation , Airports , Air traffic , Exhaust emissions , Mobile pollutant sources , Air pollution , Traffic congestion , Traffic volume , Traffic simulation , Urban transportation , Calibration , Algorithms , Surveys , Implementation , Case studies , Travel demand , Forecasting , Air transportation
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