Home  »  Research   »   A Python tool for SUMO traffic simulation to model start-stop system for comprehensive emission analysis

Vehicle emissions have become a hot topic in recent years, especially due to their impact on air quality and the environment. Emissions produced by vehicles include carbon monoxide (CO), nitrogen oxides (NOx), particulate matter (PM), hydrocarbons (HC), and carbon dioxide (CO2), which are all harmful to the environment and human health. The burning of fossil fuels in vehicles is the main source of these emissions, which contribute to climate change and air pollution. Therefore, reducing vehicle emissions is crucial to improving air quality and mitigating climate change. Many research studies are currently focused on developing new technologies and solutions to reduce emissions from vehicles.

Vehicles equipped with a start-stop system are considered better regarding their emission. Recent studies have shown that the frequent restarting of engines can produce even higher emission rates. Analyzing the effect of start-stop system vehicles requires simulations. Our laboratory developed a novel tool for SUMO to help analyze emissions in the presence of start-stop vehicles.

With this tool, the user can easily setup a simulation. Start-stop vehicles can be inserted in a ratio based way or by a SUMO vehicle type. After the simulation is finished, the tool calculates the emissions both for the regular and the start-stop scenarios. Results are stored in standard SUMO emission outputs and the difference is also shown on a bar plot. The code can be altered easily if further developments are required.

Get the tool from our GitHub repository: https://github.com/bmetrafficlab/SUMO_start_stop_system

Written by: BME Traffic Lab | Date: 16/02/2024 6:30 PM