Analysis of the Impact of Variable Speed Limits on Environmental Sustainability and Traffic Performance in Urban Networks

This work focuses on evaluating the potential of variable speed limits (VSLs) in a synthetic urban network to improve both environmental sustainability and traffic performance. The traffic system is modeled using the microscopic traffic simulator SUMO, and a physical fuel consumption and NOx emission model is used to assess the vehicles' energy efficiency. Speed limits are controlled through a nonlinear model predictive control (NMPC) approach, in which the traffic evolution and fuel consumption are respectively predicted with a macroscopic traffic model, namely the cell transmission model (CTM), and a pre-calibrated artificial neural network (ANN). The results reveal that in transient phases between different levels of congestion, the proposed eco-VSL controller is faster to decongest the network, resulting in an improvement of the environmental sustainability and the traffic performance both in the controlled network, and at its boundary roads.

Automated summary

This work focuses on evaluating the potential of using variable speed limits (VSLs) in a synthetic urban network to improve both environmental sustainability and traffic performance. The traffic system is modeled using the microscopic traffic simulator SUMO, and a physical fuel consumption and NOx emission model is used to assess the vehicles' energy efficiency. The speed limits are controlled through a nonlinear model predictive control (NMPC) approach, where the traffic evolution and fuel consumption are predicted using a macroscopic traffic model (CTM) and a pre-calibrated artificial neural network (ANN). The results show that the proposed eco-VSL controller is faster at decongesting the network during transient phases between different levels of congestion, resulting in improved environmental sustainability and traffic performance in both the controlled network and its boundary roads.