VISSIM/MOVES integration to investigate the effect of major key parameters on CO2 emissions |
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| Institution: | 1. MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology, Beijing Jiaotong University, Beijing 100044, China;2. College of Science and Technology, Texas Southern University, Houston, TX 77004, USA;3. China Railway Siyuan Survey and Design Group CO., LTD. Wuhan, Hubei 430063, China;1. CITTA, Department of Civil Engineering, University of Coimbra, Polo II, 3030-788 Coimbra, Portugal;3. CESAM & Department of Environment, University of Aveiro, 3810-193 Aveiro, Portugal;4. TEMA & Department of Mechanical Engineering, University of Aveiro, 3810-193 Aveiro, Portugal;1. Centre for Mechanical Technology and Automation, Mechanical Engineering Department, University of Aveiro, Campus Universitário de Santiago, 3810-193 Aveiro, Portugal;2. Institute for Transportation Research and Education, North Carolina State University, Centennial Campus, Raleigh, North Carolina 27606-3870, United States;1. CSIR-Indian Institute of Petroleum, Dehradun, Uttrakhand 248005, India;2. Sardar Vallabhbhai National Institute of Technology, Ichchhanath, Surat, Gujrat 395 007, India;1. Civil Engineering, University of Toronto, Canada;2. Chemical Engineering and Applied Chemistry, University of Toronto, Canada;1. Massachusetts Institute of Technology, SENSEable City Laboratory, Cambridge, MA, United States;2. Centre for Urban Science and Progress, New York University, New York City, United States;3. Wuhan University, Wuhan, Hubei, China;4. Politecnico di Milano, 32 Piazza Leonardo da Vinci, Milano, Italy;5. Center for Complex Network Research, Department of Physics, Northeastern University, Boston, United States;6. Argonne National Laboratory, National Aeronautics and Space Administration (NASA), Lemont, IL, United States;7. Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, Cambridge, MA, United States |
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| Abstract: | This paper looks at CO2 emissions on limited access highways in a microscopic and stochastic environment using an optimal design approach. Estimating vehicle emissions based on second-by-second vehicle operation allows the integration of a microscopic traffic simulation model with the latest US Environmental Protection Agency’s mobile source emissions model to improve accuracy. A factorial experiment on a test bed prototype of the I-4 urban limited access highway corridor located in Orlando, Florida was conducted to identify the optimal settings for CO2 emissions reduction and to develop a microscopic transportation emission prediction model. An exponentially decaying function towards a limiting value expressed in the freeway capacity is found to correlate with CO2 emission rates. Moreover, speeds between 55 and 60 mph show emission rate reduction effect while maintaining up to 90% of the freeway’s capacity. The results show that speed has a significant impact on CO2 emissions when detailed and microscopic analysis of vehicle operations of acceleration and deceleration are considered. |
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