Optimization of Wiedemann and Fritzsche car-following models for emission estimation |
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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. Key Laboratory of Dependable Service Computing in Cyber Physical Society of Ministry of Education, Chongqing University, Chongqing 400044, China;2. College of Automation, Chongqing University, Chongqing 400030, China;1. Institute of Systems Engineering, College of Management and Economics, Tianjin University, Tianjin 300072, China;2. MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology, Beijing Jiaotong University, Beijing 100044, China;3. Technische Universität Dresden, Institute for Transport & Economics, Würzburger Str. 35, D-01062 Dresden, Germany;1. School of Transportation, Southeast University, Nanjing 210096, China;2. Energy Research Institute, School of Chemical and Process Engineering, University of Leeds, Leeds LS2 9JT, UK;1. Université de Lyon, Lyon, France;2. IFSTTAR, COSYS-LICIT, Bron, France;3. ENTPE, LICIT, Vaulx-en-Velin, France;4. Department of Transportation Engineering, Università di Napoli Federico II, Italy;5. Institute for the Energy and Transport, European Commission – Joint Research Centre, Italy |
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| Abstract: | Recent studies have provided that the vehicle trajectories generated by car-following models may not represent the real driving characteristics, thus leading to significant emission estimation errors. In this paper, two of the most widely used car-following models, Wiedemann and Fritzsche models, were selected and analyzed based on the massive field car-following trajectories in Beijing. A numerical simulation method was designed to generate the following car’s trajectories by using the field trajectories as the input. By comparing the simulated and the filed data, the representativeness of the simulated regime fractions and VSP distributions were evaluated. Then, the mechanism of car-following models was investigated from the aspects of regime determination and the acceleration rule in each regime. Further, the regime threshold parameters and acceleration model were optimized for emission estimations. This study found that the “Following” regime threshold of SDX and the maximum acceleration in “Free Driving” regime are critical parameters for Wiedemann model. The differences between the Wiedemann simulated VSP distribution and the field one can be reduced separately by applying the optimized SDX and maximum acceleration model individually. However, a much sharper reduction was observed by optimizing both parameters simultaneously, and the emission estimation errors were further reduced, which were less than 4% in the case studies. Fritzsche model generated more realistic VSP distributions and emissions, while the maximum accelerations could be further optimized for high speed conditions. |
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| Keywords: | Car-following model VSP distribution Traffic simulation Vehicle emission |
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