Abstract
Transport emission has become an increasingly serious problem, and it is an urgent issue in sustainable transport. In this study, by constructing traffic emission models for different vehicle types and operating conditions, the changes in CO, HC, and NOx emissions of light-duty and heavy-duty vehicles before and after signal control optimization were quantified based on VISSIM simulation. The OBEAS-3000 vehicle emission testing device was used to collect data on the micro-operational characteristics of different vehicles under different operating conditions as well as traffic emission data. Based on the data collected, the VSP (Vehicle Specific Power) model combined with the VISSIM traffic simulation platform was used to calculate the emissions of light and heavy vehicles in the mixed traffic flow before and after intersection signal optimization. It is known from the study that signal control optimization has a greater impact on heavy vehicles than on light vehicles. Emissions of CO, HC, and NOx from heavy vehicles and light vehicles are all reduced, but NOx emissions from light vehicles remain largely unchanged. The research results reveal the emission patterns of light and heavy vehicles in different micro-operating conditions and establish a traffic emission model. It provides a theoretical basis for accurate traffic emission analysis and traffic flow optimization, as well as a scientific basis for the formulation of traffic management measures and emission reduction in large city transport systems.
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Fan, J., Baumann, M., Jokhio, S., Zhu, J. (2022). Evaluating the Impact of Signal Control on Emissions at Intersections. In: Bie, Y., Qu, B.X., Howlett, R.J., Jain, L.C. (eds) Smart Transportation Systems 2022. KES-STS 2022. Smart Innovation, Systems and Technologies, vol 304. Springer, Singapore. https://doi.org/10.1007/978-981-19-2813-0_11
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DOI: https://doi.org/10.1007/978-981-19-2813-0_11
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