By combining emissions modeling with traffic simulation, authorities can analyze in fine detail the environmental impact of their ITS deployments and traffic management decisions, leading to a cleaner transport network for all.
In recent years fuel emissions have gone from being a peripheral consideration in traffic engineering and management to occupying a key position in decision making.
In line with contemporary environmental regulations, the output data from an analysis of fuel consumption and pollutant emissions can sometimes be the deciding factor in cost-benefit computations.
A wide range of dynamic transportation management measures – from congestion-based road pricing to variable message signs – have been developed to manage travel demand and driver behavior.
(...)The Dutch consultancy and engineering company DHV uses Aimsun as a modeling tool in projects worldwide. It uses the model to analyse the effects of dynamic traffic measures and for traffic control design. To assess the environmental impact of traffic, DHV also uses the statistical emissions model, VERSIT+, which was developed by Dutch research organisation, TNO.
To create a tool for direct evaluation of the impact of dynamic traffic measures on air quality, DHV and TNO came together to develop a dedicated model of VERSIT+ linked to the Aimsun traffic simulation model, known as VERSIT+micro.
"VERSIT+ predicts emissions for various vehicle specifications such as fuel types, drivetrains or injection technologies, and is based on a database of 15,000 measured driving cycles mimicking all aspects of real-time driving behaviour", says Jorg van Wijk, a consultant at DHV.
The VERSIT+micro is an intelligent submodel of the very complex VERSIT+ model. Instead of 100 models for every vehicle specification, four vehicle categories were defined based on the average vehicle fleet per category. For each category, DHV and TNO composed a typical fleet composition on the Dutch urban roads and highways, taking into account the age and technology of the vehicles in a particular year. (...)
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